Overview

Dataset statistics

Number of variables29
Number of observations59288
Missing cells66801
Missing cells (%)3.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.7 MiB
Average record size in memory225.0 B

Variable types

Numeric10
Categorical15
Boolean4

Alerts

amenities has a high cardinality: 54359 distinct valuesHigh cardinality
description has a high cardinality: 58853 distinct valuesHigh cardinality
first_review has a high cardinality: 2484 distinct valuesHigh cardinality
host_response_rate has a high cardinality: 77 distinct valuesHigh cardinality
host_since has a high cardinality: 3051 distinct valuesHigh cardinality
last_review has a high cardinality: 1313 distinct valuesHigh cardinality
name has a high cardinality: 58782 distinct valuesHigh cardinality
neighbourhood has a high cardinality: 610 distinct valuesHigh cardinality
thumbnail_url has a high cardinality: 52758 distinct valuesHigh cardinality
zipcode has a high cardinality: 747 distinct valuesHigh cardinality
accommodates is highly overall correlated with bedrooms and 2 other fieldsHigh correlation
latitude is highly overall correlated with longitude and 1 other fieldsHigh correlation
longitude is highly overall correlated with latitude and 1 other fieldsHigh correlation
bedrooms is highly overall correlated with accommodates and 1 other fieldsHigh correlation
beds is highly overall correlated with accommodates and 1 other fieldsHigh correlation
price is highly overall correlated with accommodatesHigh correlation
city is highly overall correlated with latitude and 1 other fieldsHigh correlation
property_type is highly imbalanced (68.2%)Imbalance
bed_type is highly imbalanced (89.8%)Imbalance
host_has_profile_pic is highly imbalanced (97.0%)Imbalance
host_response_rate is highly imbalanced (70.6%)Imbalance
first_review has 12662 (21.4%) missing valuesMissing
host_response_rate has 14558 (24.6%) missing valuesMissing
last_review has 12633 (21.3%) missing valuesMissing
neighbourhood has 5513 (9.3%) missing valuesMissing
review_scores_rating has 13341 (22.5%) missing valuesMissing
thumbnail_url has 6520 (11.0%) missing valuesMissing
zipcode has 789 (1.3%) missing valuesMissing
id is uniformly distributedUniform
description is uniformly distributedUniform
name is uniformly distributedUniform
thumbnail_url is uniformly distributedUniform
id has unique valuesUnique
latitude has unique valuesUnique
longitude has unique valuesUnique
number_of_reviews has 12626 (21.3%) zerosZeros
bedrooms has 5428 (9.2%) zerosZeros

Reproduction

Analysis started2023-03-07 01:13:23.925988
Analysis finished2023-03-07 01:15:07.727472
Duration1 minute and 43.8 seconds
Software versionpandas-profiling v3.6.6
Download configurationconfig.json

Variables

id
Real number (ℝ)

UNIFORM  UNIQUE 

Distinct59288
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37099.016
Minimum0
Maximum74110
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size463.3 KiB
2023-03-07T01:15:07.909284image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3703.35
Q118554.75
median37161
Q355647.25
95-th percentile70411.65
Maximum74110
Range74110
Interquartile range (IQR)37092.5

Descriptive statistics

Standard deviation21411.094
Coefficient of variation (CV)0.57713376
Kurtosis-1.2024193
Mean37099.016
Median Absolute Deviation (MAD)18544.5
Skewness-0.0034435354
Sum2.1995265 × 109
Variance4.5843496 × 108
MonotonicityNot monotonic
2023-03-07T01:15:08.219128image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46459 1
 
< 0.1%
47875 1
 
< 0.1%
53209 1
 
< 0.1%
42598 1
 
< 0.1%
10460 1
 
< 0.1%
14260 1
 
< 0.1%
2991 1
 
< 0.1%
49710 1
 
< 0.1%
21041 1
 
< 0.1%
37463 1
 
< 0.1%
Other values (59278) 59278
> 99.9%
ValueCountFrequency (%)
0 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
11 1
< 0.1%
ValueCountFrequency (%)
74110 1
< 0.1%
74109 1
< 0.1%
74108 1
< 0.1%
74107 1
< 0.1%
74104 1
< 0.1%
74103 1
< 0.1%
74099 1
< 0.1%
74098 1
< 0.1%
74095 1
< 0.1%
74093 1
< 0.1%

property_type
Categorical

Distinct33
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size463.3 KiB
Apartment
39182 
House
13193 
Condominium
 
2147
Townhouse
 
1357
Loft
 
1007
Other values (28)
 
2402

Length

Max length18
Median length9
Mean length8.0769296
Min length3

Characters and Unicode

Total characters478865
Distinct characters41
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowHouse
2nd rowApartment
3rd rowApartment
4th rowTownhouse
5th rowCondominium

Common Values

ValueCountFrequency (%)
Apartment 39182
66.1%
House 13193
 
22.3%
Condominium 2147
 
3.6%
Townhouse 1357
 
2.3%
Loft 1007
 
1.7%
Other 493
 
0.8%
Guesthouse 397
 
0.7%
Bed & Breakfast 369
 
0.6%
Bungalow 287
 
0.5%
Villa 145
 
0.2%
Other values (23) 711
 
1.2%

Length

2023-03-07T01:15:08.519940image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
apartment 39197
65.1%
house 13196
 
21.9%
condominium 2147
 
3.6%
townhouse 1357
 
2.3%
loft 1007
 
1.7%
other 493
 
0.8%
guesthouse 397
 
0.7%
369
 
0.6%
breakfast 369
 
0.6%
bed 369
 
0.6%
Other values (28) 1307
 
2.2%

Most occurring characters

ValueCountFrequency (%)
t 81138
16.9%
e 56427
11.8%
n 45271
9.5%
m 43744
9.1%
a 40723
8.5%
r 40340
8.4%
p 39271
8.2%
A 39182
8.2%
o 22241
 
4.6%
u 18119
 
3.8%
Other values (31) 52409
10.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 417642
87.2%
Uppercase Letter 59802
 
12.5%
Space Separator 920
 
0.2%
Other Punctuation 440
 
0.1%
Dash Punctuation 61
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 81138
19.4%
e 56427
13.5%
n 45271
10.8%
m 43744
10.5%
a 40723
9.8%
r 40340
9.7%
p 39271
9.4%
o 22241
 
5.3%
u 18119
 
4.3%
s 16061
 
3.8%
Other values (12) 14307
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
A 39182
65.5%
H 13256
 
22.2%
C 2291
 
3.8%
T 1443
 
2.4%
B 1133
 
1.9%
L 1008
 
1.7%
G 502
 
0.8%
O 493
 
0.8%
V 222
 
0.4%
D 113
 
0.2%
Other values (5) 159
 
0.3%
Other Punctuation
ValueCountFrequency (%)
& 369
83.9%
/ 71
 
16.1%
Space Separator
ValueCountFrequency (%)
920
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 61
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 477444
99.7%
Common 1421
 
0.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 81138
17.0%
e 56427
11.8%
n 45271
9.5%
m 43744
9.2%
a 40723
8.5%
r 40340
8.4%
p 39271
8.2%
A 39182
8.2%
o 22241
 
4.7%
u 18119
 
3.8%
Other values (27) 50988
10.7%
Common
ValueCountFrequency (%)
920
64.7%
& 369
26.0%
/ 71
 
5.0%
- 61
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 478865
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 81138
16.9%
e 56427
11.8%
n 45271
9.5%
m 43744
9.1%
a 40723
8.5%
r 40340
8.4%
p 39271
8.2%
A 39182
8.2%
o 22241
 
4.6%
u 18119
 
3.8%
Other values (31) 52409
10.9%

room_type
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size463.3 KiB
Entire home/apt
33079 
Private room
24468 
Shared room
 
1741

Length

Max length15
Median length15
Mean length13.644447
Min length11

Characters and Unicode

Total characters808952
Distinct characters17
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPrivate room
2nd rowEntire home/apt
3rd rowEntire home/apt
4th rowPrivate room
5th rowEntire home/apt

Common Values

ValueCountFrequency (%)
Entire home/apt 33079
55.8%
Private room 24468
41.3%
Shared room 1741
 
2.9%

Length

2023-03-07T01:15:08.782616image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-07T01:15:09.055602image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
entire 33079
27.9%
home/apt 33079
27.9%
room 26209
22.1%
private 24468
20.6%
shared 1741
 
1.5%

Most occurring characters

ValueCountFrequency (%)
e 92367
11.4%
t 90626
11.2%
o 85497
10.6%
r 85497
10.6%
a 59288
 
7.3%
59288
 
7.3%
m 59288
 
7.3%
i 57547
 
7.1%
h 34820
 
4.3%
p 33079
 
4.1%
Other values (7) 151655
18.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 657297
81.3%
Space Separator 59288
 
7.3%
Uppercase Letter 59288
 
7.3%
Other Punctuation 33079
 
4.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 92367
14.1%
t 90626
13.8%
o 85497
13.0%
r 85497
13.0%
a 59288
9.0%
m 59288
9.0%
i 57547
8.8%
h 34820
 
5.3%
p 33079
 
5.0%
n 33079
 
5.0%
Other values (2) 26209
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
E 33079
55.8%
P 24468
41.3%
S 1741
 
2.9%
Space Separator
ValueCountFrequency (%)
59288
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 33079
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 716585
88.6%
Common 92367
 
11.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 92367
12.9%
t 90626
12.6%
o 85497
11.9%
r 85497
11.9%
a 59288
8.3%
m 59288
8.3%
i 57547
8.0%
h 34820
 
4.9%
p 33079
 
4.6%
E 33079
 
4.6%
Other values (5) 85497
11.9%
Common
ValueCountFrequency (%)
59288
64.2%
/ 33079
35.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 808952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 92367
11.4%
t 90626
11.2%
o 85497
10.6%
r 85497
10.6%
a 59288
 
7.3%
59288
 
7.3%
m 59288
 
7.3%
i 57547
 
7.1%
h 34820
 
4.3%
p 33079
 
4.1%
Other values (7) 151655
18.7%

amenities
Categorical

Distinct54359
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Memory size463.3 KiB
{}
 
462
{"translation missing: en.hosting_amenity_49","translation missing: en.hosting_amenity_50"}
 
100
{"Family/kid friendly"}
 
86
{TV,"Cable TV",Internet,"Wireless Internet","Air conditioning",Kitchen,"Pets allowed",Doorman,Gym,Elevator,Heating,"Family/kid friendly",Washer,Dryer,"Smoke detector","Carbon monoxide detector",Essentials,Shampoo,"24-hour check-in",Hangers,"Hair dryer",Iron,"Laptop friendly workspace","Self Check-In",Doorman}
 
22
{"Pets allowed","Family/kid friendly"}
 
21
Other values (54354)
58597 

Length

Max length1496
Median length750
Mean length268.09009
Min length2

Characters and Unicode

Total characters15894525
Distinct characters63
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51781 ?
Unique (%)87.3%

Sample

1st row{"Wireless Internet","Air conditioning",Kitchen,Heating,"Family/kid friendly","Smoke detector","Carbon monoxide detector","First aid kit","Safety card","Fire extinguisher",Essentials}
2nd row{Internet,"Wireless Internet",Kitchen,Heating,"Smoke detector","Carbon monoxide detector","Fire extinguisher","Lock on bedroom door","translation missing: en.hosting_amenity_49","translation missing: en.hosting_amenity_50"}
3rd row{TV,Internet,"Wireless Internet","Air conditioning","Wheelchair accessible",Kitchen,"Pets allowed",Elevator,"Buzzer/wireless intercom",Heating,"Family/kid friendly",Washer,Dryer,"Smoke detector","Carbon monoxide detector","First aid kit","Safety card","Fire extinguisher",Essentials,Shampoo,"24-hour check-in",Hangers,Iron,"Laptop friendly workspace"}
4th row{"Wireless Internet","Air conditioning","Pets live on this property",Cat(s),"Hot tub",Heating,"Smoke detector","Carbon monoxide detector",Essentials,Shampoo,"Lock on bedroom door",Hangers,"Hair dryer","Laptop friendly workspace","translation missing: en.hosting_amenity_49","translation missing: en.hosting_amenity_50"}
5th row{TV,"Cable TV",Internet,"Wireless Internet","Air conditioning",Kitchen,"Free parking on premises","Buzzer/wireless intercom",Heating,"Family/kid friendly",Washer,Dryer,"Smoke detector","Carbon monoxide detector",Essentials,Shampoo,Hangers,"Hair dryer",Iron}

Common Values

ValueCountFrequency (%)
{} 462
 
0.8%
{"translation missing: en.hosting_amenity_49","translation missing: en.hosting_amenity_50"} 100
 
0.2%
{"Family/kid friendly"} 86
 
0.1%
{TV,"Cable TV",Internet,"Wireless Internet","Air conditioning",Kitchen,"Pets allowed",Doorman,Gym,Elevator,Heating,"Family/kid friendly",Washer,Dryer,"Smoke detector","Carbon monoxide detector",Essentials,Shampoo,"24-hour check-in",Hangers,"Hair dryer",Iron,"Laptop friendly workspace","Self Check-In",Doorman} 22
 
< 0.1%
{"Pets allowed","Family/kid friendly"} 21
 
< 0.1%
{TV,"Cable TV",Internet,"Wireless Internet","Air conditioning",Kitchen,"Free parking on premises",Heating,"Family/kid friendly",Washer,Dryer,"Smoke detector","Carbon monoxide detector","First aid kit","Safety card","Fire extinguisher",Essentials,Shampoo,"24-hour check-in",Hangers,"Hair dryer",Iron,"Laptop friendly workspace"} 19
 
< 0.1%
{TV,"Cable TV","Wireless Internet","Air conditioning",Pool,Kitchen,"Pets allowed",Gym,Elevator,Heating,"Family/kid friendly",Washer,Dryer,"Smoke detector","Carbon monoxide detector",Essentials,Shampoo,Hangers,"Hair dryer",Iron,"Laptop friendly workspace","Self Check-In",Doorman,Bathtub,"Hot water","Bed linens",Refrigerator,Oven,Stove,"Long term stays allowed"} 18
 
< 0.1%
{Internet,"Wireless Internet","Air conditioning",Kitchen,Heating} 17
 
< 0.1%
{TV,"Cable TV",Internet,"Wireless Internet","Air conditioning",Kitchen,Heating} 17
 
< 0.1%
{TV,"Cable TV",Internet,"Wireless Internet","Air conditioning",Kitchen,"Buzzer/wireless intercom",Heating} 16
 
< 0.1%
Other values (54349) 58510
98.7%

Length

2023-03-07T01:15:09.313119image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
internet","air 43328
 
4.9%
on 41324
 
4.7%
monoxide 37780
 
4.3%
detector","carbon 37354
 
4.3%
missing 36673
 
4.2%
friendly 35333
 
4.0%
dryer",iron,"laptop 23351
 
2.7%
aid 22070
 
2.5%
detector","first 21576
 
2.5%
parking 19045
 
2.2%
Other values (6035) 560306
63.8%

Most occurring characters

ValueCountFrequency (%)
e 1531064
 
9.6%
" 1124296
 
7.1%
n 1114315
 
7.0%
i 1099843
 
6.9%
r 1092591
 
6.9%
, 984708
 
6.2%
t 970945
 
6.1%
o 886049
 
5.6%
818852
 
5.2%
s 731167
 
4.6%
Other values (53) 5540695
34.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 11343928
71.4%
Other Punctuation 2226613
 
14.0%
Uppercase Letter 1149239
 
7.2%
Space Separator 818852
 
5.2%
Decimal Number 103652
 
0.7%
Connector Punctuation 73346
 
0.5%
Open Punctuation 66783
 
0.4%
Close Punctuation 66783
 
0.4%
Dash Punctuation 43051
 
0.3%
Final Punctuation 2278
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1531064
13.5%
n 1114315
9.8%
i 1099843
9.7%
r 1092591
9.6%
t 970945
8.6%
o 886049
 
7.8%
s 731167
 
6.4%
a 725073
 
6.4%
d 410349
 
3.6%
l 389059
 
3.4%
Other values (14) 2393473
21.1%
Uppercase Letter
ValueCountFrequency (%)
I 142430
12.4%
H 137911
12.0%
S 120187
10.5%
W 98477
8.6%
F 95997
8.4%
C 77021
 
6.7%
E 68366
 
5.9%
T 61455
 
5.3%
V 61426
 
5.3%
L 56706
 
4.9%
Other values (10) 229263
19.9%
Other Punctuation
ValueCountFrequency (%)
" 1124296
50.5%
, 984708
44.2%
/ 44110
 
2.0%
. 36673
 
1.6%
: 36673
 
1.6%
& 153
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
4 31540
30.4%
0 20286
19.6%
5 20286
19.6%
9 16387
15.8%
2 15153
14.6%
Open Punctuation
ValueCountFrequency (%)
{ 59288
88.8%
( 7495
 
11.2%
Close Punctuation
ValueCountFrequency (%)
} 59288
88.8%
) 7495
 
11.2%
Space Separator
ValueCountFrequency (%)
818852
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 73346
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 43051
100.0%
Final Punctuation
ValueCountFrequency (%)
2278
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 12493167
78.6%
Common 3401358
 
21.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1531064
12.3%
n 1114315
 
8.9%
i 1099843
 
8.8%
r 1092591
 
8.7%
t 970945
 
7.8%
o 886049
 
7.1%
s 731167
 
5.9%
a 725073
 
5.8%
d 410349
 
3.3%
l 389059
 
3.1%
Other values (34) 3542712
28.4%
Common
ValueCountFrequency (%)
" 1124296
33.1%
, 984708
29.0%
818852
24.1%
_ 73346
 
2.2%
{ 59288
 
1.7%
} 59288
 
1.7%
/ 44110
 
1.3%
- 43051
 
1.3%
. 36673
 
1.1%
: 36673
 
1.1%
Other values (9) 121073
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15892247
> 99.9%
Punctuation 2278
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 1531064
 
9.6%
" 1124296
 
7.1%
n 1114315
 
7.0%
i 1099843
 
6.9%
r 1092591
 
6.9%
, 984708
 
6.2%
t 970945
 
6.1%
o 886049
 
5.6%
818852
 
5.2%
s 731167
 
4.6%
Other values (52) 5538417
34.8%
Punctuation
ValueCountFrequency (%)
2278
100.0%

accommodates
Real number (ℝ)

Distinct16
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1547025
Minimum1
Maximum16
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size463.3 KiB
2023-03-07T01:15:09.572887image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q34
95-th percentile7
Maximum16
Range15
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.1534997
Coefficient of variation (CV)0.68263162
Kurtosis7.4543234
Mean3.1547025
Median Absolute Deviation (MAD)1
Skewness2.2346389
Sum187036
Variance4.6375608
MonotonicityNot monotonic
2023-03-07T01:15:09.797009image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
2 25467
43.0%
4 9654
 
16.3%
1 7555
 
12.7%
3 6245
 
10.5%
6 4024
 
6.8%
5 2742
 
4.6%
8 1403
 
2.4%
7 738
 
1.2%
10 569
 
1.0%
16 241
 
0.4%
Other values (6) 650
 
1.1%
ValueCountFrequency (%)
1 7555
 
12.7%
2 25467
43.0%
3 6245
 
10.5%
4 9654
 
16.3%
5 2742
 
4.6%
6 4024
 
6.8%
7 738
 
1.2%
8 1403
 
2.4%
9 219
 
0.4%
10 569
 
1.0%
ValueCountFrequency (%)
16 241
 
0.4%
15 43
 
0.1%
14 84
 
0.1%
13 31
 
0.1%
12 208
 
0.4%
11 65
 
0.1%
10 569
1.0%
9 219
 
0.4%
8 1403
2.4%
7 738
1.2%

bathrooms
Real number (ℝ)

Distinct17
Distinct (%)< 0.1%
Missing155
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean1.2368136
Minimum0
Maximum8
Zeros161
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size463.3 KiB
2023-03-07T01:15:10.030192image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile2
Maximum8
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.58381474
Coefficient of variation (CV)0.4720313
Kurtosis22.632889
Mean1.2368136
Median Absolute Deviation (MAD)0
Skewness3.7081017
Sum73136.5
Variance0.34083965
MonotonicityNot monotonic
2023-03-07T01:15:10.266279image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
1 46378
78.2%
2 6421
 
10.8%
1.5 3063
 
5.2%
2.5 1262
 
2.1%
3 844
 
1.4%
3.5 357
 
0.6%
4 227
 
0.4%
0.5 170
 
0.3%
0 161
 
0.3%
4.5 84
 
0.1%
Other values (7) 166
 
0.3%
(Missing) 155
 
0.3%
ValueCountFrequency (%)
0 161
 
0.3%
0.5 170
 
0.3%
1 46378
78.2%
1.5 3063
 
5.2%
2 6421
 
10.8%
2.5 1262
 
2.1%
3 844
 
1.4%
3.5 357
 
0.6%
4 227
 
0.4%
4.5 84
 
0.1%
ValueCountFrequency (%)
8 36
 
0.1%
7.5 5
 
< 0.1%
7 6
 
< 0.1%
6.5 10
 
< 0.1%
6 19
 
< 0.1%
5.5 36
 
0.1%
5 54
 
0.1%
4.5 84
 
0.1%
4 227
0.4%
3.5 357
0.6%

bed_type
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size463.3 KiB
Real Bed
57628 
Futon
 
596
Pull-out Sofa
 
467
Airbed
 
373
Couch
 
224

Length

Max length13
Median length8
Mean length7.985309
Min length5

Characters and Unicode

Total characters473433
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowReal Bed
2nd rowReal Bed
3rd rowReal Bed
4th rowReal Bed
5th rowReal Bed

Common Values

ValueCountFrequency (%)
Real Bed 57628
97.2%
Futon 596
 
1.0%
Pull-out Sofa 467
 
0.8%
Airbed 373
 
0.6%
Couch 224
 
0.4%

Length

2023-03-07T01:15:10.531813image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-07T01:15:10.784503image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
real 57628
49.1%
bed 57628
49.1%
futon 596
 
0.5%
pull-out 467
 
0.4%
sofa 467
 
0.4%
airbed 373
 
0.3%
couch 224
 
0.2%

Most occurring characters

ValueCountFrequency (%)
e 115629
24.4%
l 58562
12.4%
a 58095
12.3%
58095
12.3%
d 58001
12.3%
R 57628
12.2%
B 57628
12.2%
o 1754
 
0.4%
u 1754
 
0.4%
t 1063
 
0.2%
Other values (13) 5224
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 297488
62.8%
Uppercase Letter 117383
 
24.8%
Space Separator 58095
 
12.3%
Dash Punctuation 467
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 115629
38.9%
l 58562
19.7%
a 58095
19.5%
d 58001
19.5%
o 1754
 
0.6%
u 1754
 
0.6%
t 1063
 
0.4%
n 596
 
0.2%
f 467
 
0.2%
i 373
 
0.1%
Other values (4) 1194
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
R 57628
49.1%
B 57628
49.1%
F 596
 
0.5%
P 467
 
0.4%
S 467
 
0.4%
A 373
 
0.3%
C 224
 
0.2%
Space Separator
ValueCountFrequency (%)
58095
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 467
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 414871
87.6%
Common 58562
 
12.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 115629
27.9%
l 58562
14.1%
a 58095
14.0%
d 58001
14.0%
R 57628
13.9%
B 57628
13.9%
o 1754
 
0.4%
u 1754
 
0.4%
t 1063
 
0.3%
n 596
 
0.1%
Other values (11) 4161
 
1.0%
Common
ValueCountFrequency (%)
58095
99.2%
- 467
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 473433
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 115629
24.4%
l 58562
12.4%
a 58095
12.3%
58095
12.3%
d 58001
12.3%
R 57628
12.2%
B 57628
12.2%
o 1754
 
0.4%
u 1754
 
0.4%
t 1063
 
0.2%
Other values (13) 5224
 
1.1%
Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size463.3 KiB
strict
25869 
flexible
18082 
moderate
15242 
super_strict_30
 
84
super_strict_60
 
11

Length

Max length15
Median length8
Mean length7.1385609
Min length6

Characters and Unicode

Total characters423231
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowstrict
2nd rowstrict
3rd rowstrict
4th rowstrict
5th rowstrict

Common Values

ValueCountFrequency (%)
strict 25869
43.6%
flexible 18082
30.5%
moderate 15242
25.7%
super_strict_30 84
 
0.1%
super_strict_60 11
 
< 0.1%

Length

2023-03-07T01:15:10.979042image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-07T01:15:11.229323image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
strict 25869
43.6%
flexible 18082
30.5%
moderate 15242
25.7%
super_strict_30 84
 
0.1%
super_strict_60 11
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
t 67170
15.9%
e 66743
15.8%
i 44046
10.4%
r 41301
9.8%
l 36164
8.5%
s 26059
 
6.2%
c 25964
 
6.1%
f 18082
 
4.3%
x 18082
 
4.3%
b 18082
 
4.3%
Other values (10) 61538
14.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 422851
99.9%
Connector Punctuation 190
 
< 0.1%
Decimal Number 190
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 67170
15.9%
e 66743
15.8%
i 44046
10.4%
r 41301
9.8%
l 36164
8.6%
s 26059
 
6.2%
c 25964
 
6.1%
f 18082
 
4.3%
x 18082
 
4.3%
b 18082
 
4.3%
Other values (6) 61158
14.5%
Decimal Number
ValueCountFrequency (%)
0 95
50.0%
3 84
44.2%
6 11
 
5.8%
Connector Punctuation
ValueCountFrequency (%)
_ 190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 422851
99.9%
Common 380
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 67170
15.9%
e 66743
15.8%
i 44046
10.4%
r 41301
9.8%
l 36164
8.6%
s 26059
 
6.2%
c 25964
 
6.1%
f 18082
 
4.3%
x 18082
 
4.3%
b 18082
 
4.3%
Other values (6) 61158
14.5%
Common
ValueCountFrequency (%)
_ 190
50.0%
0 95
25.0%
3 84
22.1%
6 11
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 423231
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 67170
15.9%
e 66743
15.8%
i 44046
10.4%
r 41301
9.8%
l 36164
8.5%
s 26059
 
6.2%
c 25964
 
6.1%
f 18082
 
4.3%
x 18082
 
4.3%
b 18082
 
4.3%
Other values (10) 61538
14.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size58.0 KiB
True
43543 
False
15745 
ValueCountFrequency (%)
True 43543
73.4%
False 15745
 
26.6%
2023-03-07T01:15:11.436070image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

city
Categorical

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size463.3 KiB
NYC
25886 
LA
17973 
SF
5139 
DC
4554 
Chicago
3008 

Length

Max length7
Median length6
Mean length2.8743422
Min length2

Characters and Unicode

Total characters170414
Distinct characters18
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNYC
2nd rowLA
3rd rowNYC
4th rowLA
5th rowChicago

Common Values

ValueCountFrequency (%)
NYC 25886
43.7%
LA 17973
30.3%
SF 5139
 
8.7%
DC 4554
 
7.7%
Chicago 3008
 
5.1%
Boston 2728
 
4.6%

Length

2023-03-07T01:15:11.626820image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-07T01:15:11.872236image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
nyc 25886
43.7%
la 17973
30.3%
sf 5139
 
8.7%
dc 4554
 
7.7%
chicago 3008
 
5.1%
boston 2728
 
4.6%

Most occurring characters

ValueCountFrequency (%)
C 33448
19.6%
N 25886
15.2%
Y 25886
15.2%
L 17973
10.5%
A 17973
10.5%
o 8464
 
5.0%
S 5139
 
3.0%
F 5139
 
3.0%
D 4554
 
2.7%
a 3008
 
1.8%
Other values (8) 22944
13.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 138726
81.4%
Lowercase Letter 31688
 
18.6%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 33448
24.1%
N 25886
18.7%
Y 25886
18.7%
L 17973
13.0%
A 17973
13.0%
S 5139
 
3.7%
F 5139
 
3.7%
D 4554
 
3.3%
B 2728
 
2.0%
Lowercase Letter
ValueCountFrequency (%)
o 8464
26.7%
a 3008
 
9.5%
g 3008
 
9.5%
i 3008
 
9.5%
c 3008
 
9.5%
h 3008
 
9.5%
s 2728
 
8.6%
t 2728
 
8.6%
n 2728
 
8.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 170414
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
C 33448
19.6%
N 25886
15.2%
Y 25886
15.2%
L 17973
10.5%
A 17973
10.5%
o 8464
 
5.0%
S 5139
 
3.0%
F 5139
 
3.0%
D 4554
 
2.7%
a 3008
 
1.8%
Other values (8) 22944
13.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 170414
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
C 33448
19.6%
N 25886
15.2%
Y 25886
15.2%
L 17973
10.5%
A 17973
10.5%
o 8464
 
5.0%
S 5139
 
3.0%
F 5139
 
3.0%
D 4554
 
2.7%
a 3008
 
1.8%
Other values (8) 22944
13.5%

description
Categorical

HIGH CARDINALITY  UNIFORM 

Distinct58853
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size463.3 KiB
Private room in the heart of Little Italy with FREE PARKING :) You will have your own personal door code and may arrive at ANY time you would like and as late as you wish. You can store your luggage in the closet before check-in and after check-out times :) Price adapts to demand, my rates change constantly - every night is different! Put your dates in the calendar, with the number of guests, and what you see is what you'll pay :) The neighborhood is extremely safe even at night :) Restaurants and bars are right round the corner, both upscale and casual. This room is 6 minutes away by car or uber to Chicago's famous Willis (Sears) tower. Uber costs about $7. If you are arriving by car, I am providing free resident parking passes for anywhere in the area. (Yes, that means you can drive a few blocks and still park anywhere you want!) The room will be solely yours for the time you'll stay in the Windy City. Shall you have any concerns or need any tips from the local, I'll always be happy
 
7
Hello, I've been running guest house for Koreans visiting U.S. for 3years, and recently decided to run this place for other travelers also. There are 10 room in the house. They are mostly dormitory rooms and couple of couple room and family room. This places are our women's dormitory in third floor. There are three rooms, but no doors. It is basically open space. There are 2 beds in two rooms and 4 in one room. I do not have closet in this room but there are hangers and mini shelves. My travelers usually put their baggage on the floor. There is one full bathroom only for women in 2nd floor, which you will be sharing with other women guests. Right next that bathroom, there is unisex half bathroom. All bathrooms have hair dryers. You cannot use kitchen, but you can use refrigerator. I offer breakfast every morning from 7-10 am. Bread, cereal, fruits, coffee, milk and juice will be served. You can eat take-out food in the kitchen, but please wash dishes that you used and put trash in the
 
6
Welcome to RMH, a co-ed hostel vibe home for exploring travelers or working individuals needing temporary housing. (Guests access is from 3pm to 11am daily). NON-SMOKERS ONLY! Host & small dog live on property. NOTE: Guests' bedroom is dog free. GUARANTEED In Our Home: *You receive a clean home in a safe neighborhood, clean sheets, pillow, towel and covers. **You MUST Read House Rules BEFORE Booking :) ***IMPORTANT ***SMOKERS who book: reservation cancelled upon arrival + NO Refund. The bedroom is very large with enough space for everyone (6 guests) to have peace and quiet. The kitchen and bath are very spacious. Guests will have their own keys and have access to the bedroom in which they stay, kitchen, bathroom, living room and deck. OPTIONAL: (Normal Check IN is 3pm, Check OUT is 10am) If you would like an EARLY CHECK IN before 3pm ($25 fee) Guests trying to check in after 10pm will need to get pre-approval from host and pay the late check in fee of $25. There is no key box and no gu
 
5
OutpostClub is a network of Coliving locations throughout NewYork. We built it to make it super easy to move to NewYork, and to provide cool convenient places for cheap. Coliving - is a shared housing model - where you share kitchen, living rooms, common spaces with others, having private or shared bedrooms of your choice. Everything is included in the flat fee - utilities, furniture, supplies, events. Book Now, grab your suitcase and move into the House, meet people who will become your friends Coliving Club is a beautifully curated living space in New York with a wide range of amenities such as free workspace with printer and scanner, hi-speed Wi-Fi, fully equipped kitchen, dinner and living space, private backyard, individual safe, coffee, tea, soda, shampoo, shower gel, hand soap, towels and much more! Everything is included in our flat fee. Here we thoroughly picked every detail so that you feel cozy. Expect a great night's sleep with our made in USA memory foam mattresses by Broo
 
5
Great location
 
4
Other values (58848)
59261 

Length

Max length1000
Median length1000
Mean length762.86768
Min length1

Characters and Unicode

Total characters45228899
Distinct characters2821
Distinct categories22 ?
Distinct scripts14 ?
Distinct blocks25 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58499 ?
Unique (%)98.7%

Sample

1st rowThis is a comfortable, simple beautiful room, one block away from Sunset Park. Clean, cozy and furnished for the comfort of our guests. This is a comfortable a very simple beautiful room one block away from Sunset Park. Clean, cozy and furnished to be a comfortable as possible for our guests. We are centrally located between both 5th and 6th Avenue shops, restaurants, cafes and markets. Sightseeing nearby, include Prospect Park, Brooklyn Museum, Brooklyn Botanical Gardens, Brooklyn Academy of Music, which are all easily commutable via train or cab. We are just 5 blocks away from the D, N, M and R train. Manhattan within 15 minutes or Midtown in 20 minutes. WE PROVIDE: Full side bed with sheets and towel provide. HDTV, WIFI and a warm welcome! You will have full access to the kitchen with microwave, fridge, two burner portable stove, coffee maker, toaster and all cooking ware. and if the weather is behaving good feel free to use our wonderful backyard. Check-in is at 3pm Check-out is a
2nd rowRenovated clean & modern 1 bedroom in the heart of Venice Beach. Located on a quiet, cozy street that's just moments from the Boardwalk. This is the perfect listing if you're a respectful, responsible guy/gal! This is the front apartment on the first floor of a former single-family home. It was renovated just a few years ago with new flooring, appliances, etc. Lots of natural light and ocean breezes. Furnished in a clean, modern aesthetic with relaxation in mind. Guests have access to wifi, kitchen, basic pantry supplies, clean linens/towels, and a bit of closet space. Out of respect to my neighbors, shared washer/dryer and communal outdoor spaces are off-limits. I'll meet with you to get you settled in. After that, the place is all yours. I'll be available by phone and text if any issues arise. This is a very walkable neighborhood with lots of great restaurants and nightlife. Oh, and the beach, of course. The Venice Boardwalk is just around the corner and it's a 10-minute walk to Abbo
3rd rowMy studio is located in the heart of Bensonhurst - Little Italy and small Chinatown of Brooklyn. It's cozy and comfortable place to stay short term! My studio is located in the heart of Bensonhurst - Little Italy and small Chinatown of Brooklyn. It's cozy and comfortable place to stay short term! The space is great for a small party and it's well equipped with amenities and it has pretty much everything a guest might need for a good rest. The guest has a access to an entire home! I am always available for communication, any time a guest needs help I will be there 24/7 The area is very multicultural; it's just a 5 min walk from Bensonhurst park and Verrazano bridge Boardwalk- the park itself very close to the ocean. The area has all possible shopping and the prices are the lowest in town! The commute is very easy - it's a plenty of buses around BK plus D/N train and only 35 minutes from midtown Manhattan! Car services are all over as well! There's a fire escape outside the window - plea
4th row我们位于洛杉矶圣盖博市,距离夏威夷超市,99大华超市,顺发超市(全部为华人超市,语言沟通无障碍)步行十分钟距离,离costco,targte,walmart圣盖博医院丶嘉惠尔医院不到十分钟的车程。封闭小区,安全铁门。交通便利,超市丶餐馆丶医院丶公交车站都在步行距离,即使无车代步依然出入自如,让您出行方便。我们了解您拎包入住的需求,设施齐全,水电网络,家电家具,床上用品一应俱全,干净卫生,让您居住安全无忧。独立卫生间。 Private bathroom。 本房间内有两张床,一张Queen Size,一张Twin Size. zh.airbnb.com/c/shaohuac2 用此链接注册可获得$30美元住房基金用于订房! 我们位于洛杉矶圣盖博市,距离夏威夷超市,九九大华超市,顺发超市(全部为华人超市,语言沟通无障碍)步行十分钟距离,离costco,target,walmart圣盖博医院丶嘉惠尔医院不到十分钟的车程。封闭小区,安全铁门。交通便利,超市丶餐馆丶医院丶公交车站都在步行距离,即使无车代步依然出入自如,让您出行方便。 我们了解您拎包入住的需求,设施齐全,水电煤网络,家电家具,床上用品一应俱全,同,贴心舒适丶干净卫生,让您居住安全无忧。 自有卫生间,大浴室,冲浪浴缸! 全新家私以及床上用品,包水电,宽带,24小时热水,楼下有专门的客用微波炉以及冰箱。 1 mile to the GYM, AMC theater & shops in San Gabriel Square > 3 mile to CSULA & ELAC (bus #70 & 770) > 5 mile to USC medical center (bus #70 to the door) > 7 mile to downtown L A > 10 mile to USC Main campus > 12 mile to Hollywood area & Thai Town
5th rowLocated in the heart of the bustling Woodlawn/Hyde park Area. Just a 10 minute drive to the beaches and running trails of Lake Michigan and Grant Park. Conveniently located near public transit and the well renowned Museum of Science and Industry. UPSCALE AMENITIES!!! Why stay at a hotel! The location of this condo is within walking distance of the University of Chicago. The renovated brick condominium features 2 Bedrooms with en Suite Bathrooms. The Master Bedroom is furnished with a REAL Queen size bed. The 2nd bedroom has a REAL QUEEN SIZE BED. The Master Bathroom is equipped with a jacuzzi bathtub to provide additional relaxation during your vacation or staycation. The furnished guestrooms include flat screen television and dvd player. The unit has a modern kitchen, washer and dryer, common area and sunroom. There is also a shared rear patio. Everything in the unit is included in your stay. Ample Parking , Internet, linens, etc, etc. We are a text or phone call away if help is

Common Values

ValueCountFrequency (%)
Private room in the heart of Little Italy with FREE PARKING :) You will have your own personal door code and may arrive at ANY time you would like and as late as you wish. You can store your luggage in the closet before check-in and after check-out times :) Price adapts to demand, my rates change constantly - every night is different! Put your dates in the calendar, with the number of guests, and what you see is what you'll pay :) The neighborhood is extremely safe even at night :) Restaurants and bars are right round the corner, both upscale and casual. This room is 6 minutes away by car or uber to Chicago's famous Willis (Sears) tower. Uber costs about $7. If you are arriving by car, I am providing free resident parking passes for anywhere in the area. (Yes, that means you can drive a few blocks and still park anywhere you want!) The room will be solely yours for the time you'll stay in the Windy City. Shall you have any concerns or need any tips from the local, I'll always be happy 7
 
< 0.1%
Hello, I've been running guest house for Koreans visiting U.S. for 3years, and recently decided to run this place for other travelers also. There are 10 room in the house. They are mostly dormitory rooms and couple of couple room and family room. This places are our women's dormitory in third floor. There are three rooms, but no doors. It is basically open space. There are 2 beds in two rooms and 4 in one room. I do not have closet in this room but there are hangers and mini shelves. My travelers usually put their baggage on the floor. There is one full bathroom only for women in 2nd floor, which you will be sharing with other women guests. Right next that bathroom, there is unisex half bathroom. All bathrooms have hair dryers. You cannot use kitchen, but you can use refrigerator. I offer breakfast every morning from 7-10 am. Bread, cereal, fruits, coffee, milk and juice will be served. You can eat take-out food in the kitchen, but please wash dishes that you used and put trash in the 6
 
< 0.1%
Welcome to RMH, a co-ed hostel vibe home for exploring travelers or working individuals needing temporary housing. (Guests access is from 3pm to 11am daily). NON-SMOKERS ONLY! Host & small dog live on property. NOTE: Guests' bedroom is dog free. GUARANTEED In Our Home: *You receive a clean home in a safe neighborhood, clean sheets, pillow, towel and covers. **You MUST Read House Rules BEFORE Booking :) ***IMPORTANT ***SMOKERS who book: reservation cancelled upon arrival + NO Refund. The bedroom is very large with enough space for everyone (6 guests) to have peace and quiet. The kitchen and bath are very spacious. Guests will have their own keys and have access to the bedroom in which they stay, kitchen, bathroom, living room and deck. OPTIONAL: (Normal Check IN is 3pm, Check OUT is 10am) If you would like an EARLY CHECK IN before 3pm ($25 fee) Guests trying to check in after 10pm will need to get pre-approval from host and pay the late check in fee of $25. There is no key box and no gu 5
 
< 0.1%
OutpostClub is a network of Coliving locations throughout NewYork. We built it to make it super easy to move to NewYork, and to provide cool convenient places for cheap. Coliving - is a shared housing model - where you share kitchen, living rooms, common spaces with others, having private or shared bedrooms of your choice. Everything is included in the flat fee - utilities, furniture, supplies, events. Book Now, grab your suitcase and move into the House, meet people who will become your friends Coliving Club is a beautifully curated living space in New York with a wide range of amenities such as free workspace with printer and scanner, hi-speed Wi-Fi, fully equipped kitchen, dinner and living space, private backyard, individual safe, coffee, tea, soda, shampoo, shower gel, hand soap, towels and much more! Everything is included in our flat fee. Here we thoroughly picked every detail so that you feel cozy. Expect a great night's sleep with our made in USA memory foam mattresses by Broo 5
 
< 0.1%
Great location 4
 
< 0.1%
Our unique building is located in the Silicon Beach, directly across the street from (SENSITIVE CONTENTS HIDDEN) in Playa Vista. Fully remodeled designer-done 4-plex walking distance to the Playa Vista Runway, (SENSITIVE CONTENTS HIDDEN), YouTube, IMAX, Belkin, FOX, and (SENSITIVE CONTENTS HIDDEN). Two one-bedroom units and two studio units have all been remodeled by a high-end designer in 2015 Our place is good for couples, solo adventurers, and business travelers. Sorry, no pets. Units 1 & 2 are downstairs, 3 & 4 are upstairs. The building has one set of professional coin operated washer and dryer machines, shared by all four units. The laundry room is located towards the back of the building, near the back gate. You will have access to one (and only one) off-street parking spot in the back of the building. When confirming your booking, please inform the model, color and license plate of the car you will have throughout your stay - that way we can control who's illegally parked and s 4
 
< 0.1%
Spacious 2 story 4000 sqft home Enjoy fruit trees swimming pool fountain & gardens lWalking distance to mall, grocery store, movie theater & restaurants. Centrally located to Malibu, Santa Monica,Venice,Hollywood, Beverly Hills, West LA This spacious 2 story 4000 sqft home is fully furnished and beautifully decorated! Coffee and donuts are served every morning;) Please keep in mind that this is a shared space, and that your large room consists of 2 bunk beds, your own dresser, hamper, and closet space. You will have full access to the rest of the home. We provide a safe, clean, and positive environment, perfect for people relocating from out of state, students, and anyone else who needs a landing place while traveling. Near public transportation; ORANGELINE, 405, and 101 FREEWAYS. You will have full access to the rest of the home. We do have private and 2 person and or couples rooms available in the same property. Full kitchen privileges All Premium Cable and movie channels Full se 4
 
< 0.1%
Perched on the historic C&O Canal, the Georgetown House is an intimate boutique inn offering its guests 11 newly appointed rooms in the heart of quintessential Georgetown. Behind its bright red door and gray brick facade, lays a world of history unbeknownst to even some of its local visitors. Originally established and built in the 1830's, the building was initially constructed for use by the Chesapeake & Ohio Canal Company. Behind its bright red door and gray brick facade, lays a world of history unbeknownst to even some of its local visitors. Originally established and built in the 1830's, the building was initially constructed for use by the Chesapeake & Ohio Canal Company for storage of its equipment as they worked to build the canal and its lock system. Shortly thereafter it was renovated into a stable where horses or mules drawing the barges were kept below while the drivers lived above. After there was no need for mules and horses, the house was turned into a tavern. While the b 4
 
< 0.1%
My place is within walking distance to Grant Park, Soldier Field, The Field Museum, CTA's Roosevelt Stop, and Trader Joe's grocery store. You'll love my place because of the views of Lake Michigan from the living room, the convenient location in downtown Chicago's South Loop neighborhood, full-size basketball court, yoga room, 2 fitness centers and the 24/7 front desk staffed with professional security. My place is good for couples, solo adventurers, and families (with kids). Our apartments have 2 private bedrooms with shared common areas. Each bedroom has 2 single beds. The bedroom doors do lock. Up to four individuals in the space would share the living room, kitchen and bathroom. If you are interested in renting the entire apartment please let us know and we can send a special rate via Airbnb. Guests have access to building 24/7. A front desk is manned by a professional security firm that may request guest to verify authorization upon entering the building. Building is fully a 4
 
< 0.1%
At the intersection of the charming Leather District, bustling Chinatown, and the Theater District’s entertainment hub, this apartment offers countless opportunities to fully immerse yourself in Boston city life. Guests can live comfortably in a spacious living space with one bed, a fully-equipped kitchen, and soaring ceilings. Guests can also take advantage of the many amenities the building offers. 2 bedrooms, 2 bathrooms, sleeps 5 Discover unsurpassed city living in these thoughtfully designed, sophisticated apartment residences. Nestled right where Boston’s Leather District, Chinatown, and the Theater District converge, you’re in the fast lane to every major Boston attraction. The 19th century brick and stone architecture that characterizes The Leather Districts’ famous South Street, provides the backdrop for quite a romantic date night. Looking for a night out with friends? The Theater District is the home to many classic theaters, musicals, concerts, ballets, and drama. And wh 4
 
< 0.1%
Other values (58843) 59241
99.9%

Length

2023-03-07T01:15:12.143322image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the 344911
 
4.5%
and 318135
 
4.1%
a 221496
 
2.9%
to 195333
 
2.5%
is 153255
 
2.0%
in 145961
 
1.9%
of 127138
 
1.6%
with 113636
 
1.5%
you 80621
 
1.0%
78284
 
1.0%
Other values (85069) 5955047
77.0%

Most occurring characters

ValueCountFrequency (%)
7818054
17.3%
e 3875774
 
8.6%
a 2978756
 
6.6%
o 2888672
 
6.4%
t 2812401
 
6.2%
n 2359499
 
5.2%
i 2334230
 
5.2%
r 2229636
 
4.9%
s 2108412
 
4.7%
l 1617834
 
3.6%
Other values (2811) 14205631
31.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 33549897
74.2%
Space Separator 7818655
 
17.3%
Uppercase Letter 1879269
 
4.2%
Other Punctuation 1303183
 
2.9%
Decimal Number 331937
 
0.7%
Dash Punctuation 111625
 
0.2%
Other Letter 105459
 
0.2%
Close Punctuation 51687
 
0.1%
Open Punctuation 49117
 
0.1%
Math Symbol 10498
 
< 0.1%
Other values (12) 17572
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2280
 
2.2%
1903
 
1.8%
1376
 
1.3%
1264
 
1.2%
1163
 
1.1%
1010
 
1.0%
973
 
0.9%
962
 
0.9%
957
 
0.9%
949
 
0.9%
Other values (2535) 92622
87.8%
Lowercase Letter
ValueCountFrequency (%)
e 3875774
11.6%
a 2978756
 
8.9%
o 2888672
 
8.6%
t 2812401
 
8.4%
n 2359499
 
7.0%
i 2334230
 
7.0%
r 2229636
 
6.6%
s 2108412
 
6.3%
l 1617834
 
4.8%
h 1384533
 
4.1%
Other values (81) 8960150
26.7%
Uppercase Letter
ValueCountFrequency (%)
T 195285
 
10.4%
S 135141
 
7.2%
C 125750
 
6.7%
A 123764
 
6.6%
B 113813
 
6.1%
I 113110
 
6.0%
M 98811
 
5.3%
L 89280
 
4.8%
W 85347
 
4.5%
E 84500
 
4.5%
Other values (51) 714468
38.0%
Other Punctuation
ValueCountFrequency (%)
, 539756
41.4%
. 489509
37.6%
' 63218
 
4.9%
! 60392
 
4.6%
/ 53468
 
4.1%
& 25467
 
2.0%
: 22689
 
1.7%
* 15311
 
1.2%
" 10348
 
0.8%
; 7035
 
0.5%
Other values (21) 15990
 
1.2%
Decimal Number
ValueCountFrequency (%)
1 73669
22.2%
2 66917
20.2%
0 53535
16.1%
5 39529
11.9%
3 31491
9.5%
4 25896
 
7.8%
6 12847
 
3.9%
7 10508
 
3.2%
8 8847
 
2.7%
9 8696
 
2.6%
Other Symbol
ValueCountFrequency (%)
881
83.8%
° 35
 
3.3%
30
 
2.9%
24
 
2.3%
® 23
 
2.2%
21
 
2.0%
15
 
1.4%
12
 
1.1%
7
 
0.7%
© 3
 
0.3%
Math Symbol
ValueCountFrequency (%)
+ 4789
45.6%
= 3558
33.9%
~ 1055
 
10.0%
> 588
 
5.6%
| 409
 
3.9%
42
 
0.4%
× 32
 
0.3%
< 23
 
0.2%
2
 
< 0.1%
Nonspacing Mark
ValueCountFrequency (%)
74
85.1%
̄ 4
 
4.6%
ً 2
 
2.3%
́ 2
 
2.3%
1
 
1.1%
1
 
1.1%
1
 
1.1%
1
 
1.1%
1
 
1.1%
Open Punctuation
ValueCountFrequency (%)
( 48788
99.3%
[ 261
 
0.5%
{ 32
 
0.1%
19
 
< 0.1%
10
 
< 0.1%
5
 
< 0.1%
2
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 51355
99.4%
] 261
 
0.5%
} 38
 
0.1%
18
 
< 0.1%
10
 
< 0.1%
5
 
< 0.1%
Modifier Symbol
ValueCountFrequency (%)
` 79
32.9%
´ 60
25.0%
^ 53
22.1%
¸ 28
 
11.7%
¨ 19
 
7.9%
˚ 1
 
0.4%
Space Separator
ValueCountFrequency (%)
7818054
> 99.9%
  580
 
< 0.1%
15
 
< 0.1%
4
 
< 0.1%
2
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 110067
98.6%
872
 
0.8%
672
 
0.6%
7
 
< 0.1%
7
 
< 0.1%
Modifier Letter
ValueCountFrequency (%)
167
94.4%
4
 
2.3%
3
 
1.7%
ʼ 2
 
1.1%
1
 
0.6%
Other Number
ValueCountFrequency (%)
½ 61
54.0%
² 45
39.8%
¾ 5
 
4.4%
¼ 2
 
1.8%
Format
ValueCountFrequency (%)
­ 14
77.8%
2
 
11.1%
1
 
5.6%
 1
 
5.6%
Final Punctuation
ValueCountFrequency (%)
8679
94.5%
496
 
5.4%
» 8
 
0.1%
Currency Symbol
ValueCountFrequency (%)
$ 4020
99.9%
2
 
< 0.1%
2
 
< 0.1%
Initial Punctuation
ValueCountFrequency (%)
369
90.2%
40
 
9.8%
Control
ValueCountFrequency (%)
108
99.1%
 1
 
0.9%
Connector Punctuation
ValueCountFrequency (%)
_ 2160
100.0%
Spacing Mark
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 35425514
78.3%
Common 9694179
 
21.4%
Han 100904
 
0.2%
Cyrillic 3668
 
< 0.1%
Hiragana 2387
 
< 0.1%
Katakana 1328
 
< 0.1%
Hangul 771
 
< 0.1%
Inherited 83
 
< 0.1%
Arabic 24
 
< 0.1%
Thai 18
 
< 0.1%
Other values (4) 23
 
< 0.1%

Most frequent character per script

Han
ValueCountFrequency (%)
2280
 
2.3%
1903
 
1.9%
1376
 
1.4%
1264
 
1.3%
1163
 
1.2%
1010
 
1.0%
973
 
1.0%
962
 
1.0%
957
 
0.9%
949
 
0.9%
Other values (2150) 88067
87.3%
Hangul
ValueCountFrequency (%)
31
 
4.0%
30
 
3.9%
21
 
2.7%
20
 
2.6%
18
 
2.3%
17
 
2.2%
16
 
2.1%
16
 
2.1%
15
 
1.9%
13
 
1.7%
Other values (212) 574
74.4%
Common
ValueCountFrequency (%)
7818054
80.6%
, 539756
 
5.6%
. 489509
 
5.0%
- 110067
 
1.1%
1 73669
 
0.8%
2 66917
 
0.7%
' 63218
 
0.7%
! 60392
 
0.6%
0 53535
 
0.6%
/ 53468
 
0.6%
Other values (101) 365594
 
3.8%
Latin
ValueCountFrequency (%)
e 3875774
 
10.9%
a 2978756
 
8.4%
o 2888672
 
8.2%
t 2812401
 
7.9%
n 2359499
 
6.7%
i 2334230
 
6.6%
r 2229636
 
6.3%
s 2108412
 
6.0%
l 1617834
 
4.6%
h 1384533
 
3.9%
Other values (89) 10835767
30.6%
Katakana
ValueCountFrequency (%)
113
 
8.5%
83
 
6.2%
76
 
5.7%
65
 
4.9%
60
 
4.5%
59
 
4.4%
51
 
3.8%
50
 
3.8%
37
 
2.8%
34
 
2.6%
Other values (62) 700
52.7%
Hiragana
ValueCountFrequency (%)
184
 
7.7%
182
 
7.6%
171
 
7.2%
154
 
6.5%
136
 
5.7%
107
 
4.5%
107
 
4.5%
103
 
4.3%
88
 
3.7%
81
 
3.4%
Other values (51) 1074
45.0%
Cyrillic
ValueCountFrequency (%)
о 437
 
11.9%
е 301
 
8.2%
т 248
 
6.8%
а 246
 
6.7%
и 243
 
6.6%
н 221
 
6.0%
с 206
 
5.6%
м 183
 
5.0%
р 170
 
4.6%
в 142
 
3.9%
Other values (42) 1271
34.7%
Thai
ValueCountFrequency (%)
2
11.1%
2
11.1%
2
11.1%
2
11.1%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
Other values (4) 4
22.2%
Arabic
ValueCountFrequency (%)
ت 3
12.5%
ر 3
12.5%
ح 3
12.5%
ب 3
12.5%
ي 3
12.5%
ه 2
8.3%
ل 2
8.3%
ا 2
8.3%
أ 1
 
4.2%
س 1
 
4.2%
Devanagari
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
Inherited
ValueCountFrequency (%)
74
89.2%
̄ 4
 
4.8%
ً 2
 
2.4%
́ 2
 
2.4%
1
 
1.2%
Hebrew
ValueCountFrequency (%)
ק 2
20.0%
צ 2
20.0%
ת 2
20.0%
ע 2
20.0%
ב 2
20.0%
Greek
ValueCountFrequency (%)
ό 4
66.7%
2
33.3%
Bopomofo
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45093460
99.7%
CJK 100895
 
0.2%
Punctuation 17309
 
< 0.1%
None 7722
 
< 0.1%
Cyrillic 3668
 
< 0.1%
Hiragana 2387
 
< 0.1%
Katakana 1493
 
< 0.1%
Misc Symbols 945
 
< 0.1%
Hangul 771
 
< 0.1%
VS 74
 
< 0.1%
Other values (15) 175
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7818054
17.3%
e 3875774
 
8.6%
a 2978756
 
6.6%
o 2888672
 
6.4%
t 2812401
 
6.2%
n 2359499
 
5.2%
i 2334230
 
5.2%
r 2229636
 
4.9%
s 2108412
 
4.7%
l 1617834
 
3.6%
Other values (86) 14070192
31.2%
Punctuation
ValueCountFrequency (%)
8679
50.1%
5762
33.3%
872
 
5.0%
672
 
3.9%
496
 
2.9%
369
 
2.1%
336
 
1.9%
40
 
0.2%
15
 
0.1%
12
 
0.1%
Other values (11) 56
 
0.3%
None
ValueCountFrequency (%)
2648
34.3%
1774
23.0%
é 826
 
10.7%
  580
 
7.5%
400
 
5.2%
244
 
3.2%
· 133
 
1.7%
ñ 97
 
1.3%
à 82
 
1.1%
á 66
 
0.9%
Other values (74) 872
 
11.3%
CJK
ValueCountFrequency (%)
2280
 
2.3%
1903
 
1.9%
1376
 
1.4%
1264
 
1.3%
1163
 
1.2%
1010
 
1.0%
973
 
1.0%
962
 
1.0%
957
 
0.9%
949
 
0.9%
Other values (2145) 88058
87.3%
Misc Symbols
ValueCountFrequency (%)
881
93.2%
30
 
3.2%
15
 
1.6%
12
 
1.3%
7
 
0.7%
Cyrillic
ValueCountFrequency (%)
о 437
 
11.9%
е 301
 
8.2%
т 248
 
6.8%
а 246
 
6.7%
и 243
 
6.6%
н 221
 
6.0%
с 206
 
5.6%
м 183
 
5.0%
р 170
 
4.6%
в 142
 
3.9%
Other values (42) 1271
34.7%
Hiragana
ValueCountFrequency (%)
184
 
7.7%
182
 
7.6%
171
 
7.2%
154
 
6.5%
136
 
5.7%
107
 
4.5%
107
 
4.5%
103
 
4.3%
88
 
3.7%
81
 
3.4%
Other values (51) 1074
45.0%
Katakana
ValueCountFrequency (%)
167
 
11.2%
113
 
7.6%
83
 
5.6%
76
 
5.1%
65
 
4.4%
60
 
4.0%
59
 
4.0%
51
 
3.4%
50
 
3.3%
37
 
2.5%
Other values (59) 732
49.0%
VS
ValueCountFrequency (%)
74
100.0%
Arrows
ValueCountFrequency (%)
42
100.0%
Hangul
ValueCountFrequency (%)
31
 
4.0%
30
 
3.9%
21
 
2.7%
20
 
2.6%
18
 
2.3%
17
 
2.2%
16
 
2.1%
16
 
2.1%
15
 
1.9%
13
 
1.7%
Other values (212) 574
74.4%
Dingbats
ValueCountFrequency (%)
24
100.0%
Letterlike Symbols
ValueCountFrequency (%)
21
100.0%
Diacriticals
ValueCountFrequency (%)
̄ 4
66.7%
́ 2
33.3%
Latin Ext Additional
ValueCountFrequency (%)
4
80.0%
1
 
20.0%
Arabic
ValueCountFrequency (%)
ت 3
11.5%
ر 3
11.5%
ح 3
11.5%
ب 3
11.5%
ي 3
11.5%
ه 2
7.7%
ل 2
7.7%
ا 2
7.7%
ً 2
7.7%
أ 1
 
3.8%
Other values (2) 2
7.7%
Currency Symbols
ValueCountFrequency (%)
2
50.0%
2
50.0%
Thai
ValueCountFrequency (%)
2
11.1%
2
11.1%
2
11.1%
2
11.1%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
Other values (4) 4
22.2%
Hebrew
ValueCountFrequency (%)
ק 2
20.0%
צ 2
20.0%
ת 2
20.0%
ע 2
20.0%
ב 2
20.0%
Greek Ext
ValueCountFrequency (%)
2
100.0%
CJK Ext A
ValueCountFrequency (%)
2
40.0%
1
20.0%
1
20.0%
1
20.0%
Math Operators
ValueCountFrequency (%)
2
100.0%
Modifier Letters
ValueCountFrequency (%)
ʼ 2
66.7%
˚ 1
33.3%
Bopomofo
ValueCountFrequency (%)
1
100.0%
Devanagari
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%

first_review
Categorical

HIGH CARDINALITY  MISSING 

Distinct2484
Distinct (%)5.3%
Missing12662
Missing (%)21.4%
Memory size463.3 KiB
2017-01-01
 
232
2017-01-22
 
195
2017-01-02
 
168
2016-01-02
 
163
2017-09-04
 
154
Other values (2479)
45714 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters466260
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique345 ?
Unique (%)0.7%

Sample

1st row2015-09-24
2nd row2015-06-15
3rd row2016-01-03
4th row2016-06-16
5th row2015-07-31

Common Values

ValueCountFrequency (%)
2017-01-01 232
 
0.4%
2017-01-22 195
 
0.3%
2017-01-02 168
 
0.3%
2016-01-02 163
 
0.3%
2017-09-04 154
 
0.3%
2016-01-03 146
 
0.2%
2016-09-05 135
 
0.2%
2016-10-09 132
 
0.2%
2017-04-16 130
 
0.2%
2017-03-19 126
 
0.2%
Other values (2474) 45045
76.0%
(Missing) 12662
 
21.4%

Length

2023-03-07T01:15:12.431491image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2017-01-01 232
 
0.5%
2017-01-22 195
 
0.4%
2017-01-02 168
 
0.4%
2016-01-02 163
 
0.3%
2017-09-04 154
 
0.3%
2016-01-03 146
 
0.3%
2016-09-05 135
 
0.3%
2016-10-09 132
 
0.3%
2017-04-16 130
 
0.3%
2015-09-21 126
 
0.3%
Other values (2474) 45045
96.6%

Most occurring characters

ValueCountFrequency (%)
0 106612
22.9%
- 93252
20.0%
1 84014
18.0%
2 72650
15.6%
6 25483
 
5.5%
7 21371
 
4.6%
5 18531
 
4.0%
3 12724
 
2.7%
4 12532
 
2.7%
9 9581
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 373008
80.0%
Dash Punctuation 93252
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 106612
28.6%
1 84014
22.5%
2 72650
19.5%
6 25483
 
6.8%
7 21371
 
5.7%
5 18531
 
5.0%
3 12724
 
3.4%
4 12532
 
3.4%
9 9581
 
2.6%
8 9510
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 93252
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 466260
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 106612
22.9%
- 93252
20.0%
1 84014
18.0%
2 72650
15.6%
6 25483
 
5.5%
7 21371
 
4.6%
5 18531
 
4.0%
3 12724
 
2.7%
4 12532
 
2.7%
9 9581
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 466260
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 106612
22.9%
- 93252
20.0%
1 84014
18.0%
2 72650
15.6%
6 25483
 
5.5%
7 21371
 
4.6%
5 18531
 
4.0%
3 12724
 
2.7%
4 12532
 
2.7%
9 9581
 
2.1%
Distinct2
Distinct (%)< 0.1%
Missing151
Missing (%)0.3%
Memory size115.9 KiB
True
58953 
False
 
184
(Missing)
 
151
ValueCountFrequency (%)
True 58953
99.4%
False 184
 
0.3%
(Missing) 151
 
0.3%
2023-03-07T01:15:12.652824image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing151
Missing (%)0.3%
Memory size115.9 KiB
True
39832 
False
19305 
(Missing)
 
151
ValueCountFrequency (%)
True 39832
67.2%
False 19305
32.6%
(Missing) 151
 
0.3%
2023-03-07T01:15:12.827536image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

host_response_rate
Categorical

HIGH CARDINALITY  IMBALANCE  MISSING 

Distinct77
Distinct (%)0.2%
Missing14558
Missing (%)24.6%
Memory size463.3 KiB
100%
34634 
90%
 
1833
80%
 
886
0%
 
736
50%
 
497
Other values (72)
6144 

Length

Max length4
Median length4
Mean length3.7578359
Min length2

Characters and Unicode

Total characters168088
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st row100%
2nd row80%
3rd row100%
4th row100%
5th row100%

Common Values

ValueCountFrequency (%)
100% 34634
58.4%
90% 1833
 
3.1%
80% 886
 
1.5%
0% 736
 
1.2%
50% 497
 
0.8%
70% 402
 
0.7%
99% 365
 
0.6%
67% 340
 
0.6%
94% 336
 
0.6%
98% 335
 
0.6%
Other values (67) 4366
 
7.4%
(Missing) 14558
24.6%

Length

2023-03-07T01:15:13.034375image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
100 34634
77.4%
90 1833
 
4.1%
80 886
 
2.0%
0 736
 
1.6%
50 497
 
1.1%
70 402
 
0.9%
99 365
 
0.8%
67 340
 
0.8%
94 336
 
0.8%
98 335
 
0.7%
Other values (67) 4366
 
9.8%

Most occurring characters

ValueCountFrequency (%)
0 74050
44.1%
% 44730
26.6%
1 35017
20.8%
9 5074
 
3.0%
8 2872
 
1.7%
7 1791
 
1.1%
6 1293
 
0.8%
5 1292
 
0.8%
3 885
 
0.5%
4 607
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 123358
73.4%
Other Punctuation 44730
 
26.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 74050
60.0%
1 35017
28.4%
9 5074
 
4.1%
8 2872
 
2.3%
7 1791
 
1.5%
6 1293
 
1.0%
5 1292
 
1.0%
3 885
 
0.7%
4 607
 
0.5%
2 477
 
0.4%
Other Punctuation
ValueCountFrequency (%)
% 44730
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 168088
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 74050
44.1%
% 44730
26.6%
1 35017
20.8%
9 5074
 
3.0%
8 2872
 
1.7%
7 1791
 
1.1%
6 1293
 
0.8%
5 1292
 
0.8%
3 885
 
0.5%
4 607
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 168088
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 74050
44.1%
% 44730
26.6%
1 35017
20.8%
9 5074
 
3.0%
8 2872
 
1.7%
7 1791
 
1.1%
6 1293
 
0.8%
5 1292
 
0.8%
3 885
 
0.5%
4 607
 
0.4%

host_since
Categorical

Distinct3051
Distinct (%)5.2%
Missing151
Missing (%)0.3%
Memory size463.3 KiB
2015-03-30
 
193
2014-02-14
 
147
2016-09-16
 
72
2014-07-29
 
68
2015-12-01
 
67
Other values (3046)
58590 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters591370
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique171 ?
Unique (%)0.3%

Sample

1st row2011-09-19
2nd row2014-04-04
3rd row2015-09-02
4th row2016-03-17
5th row2015-02-10

Common Values

ValueCountFrequency (%)
2015-03-30 193
 
0.3%
2014-02-14 147
 
0.2%
2016-09-16 72
 
0.1%
2014-07-29 68
 
0.1%
2015-12-01 67
 
0.1%
2015-05-18 66
 
0.1%
2014-09-02 65
 
0.1%
2016-01-18 65
 
0.1%
2015-07-29 64
 
0.1%
2015-07-06 62
 
0.1%
Other values (3041) 58268
98.3%
(Missing) 151
 
0.3%

Length

2023-03-07T01:15:13.283664image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2015-03-30 193
 
0.3%
2014-02-14 147
 
0.2%
2016-09-16 72
 
0.1%
2014-07-29 68
 
0.1%
2015-12-01 67
 
0.1%
2015-05-18 66
 
0.1%
2014-09-02 65
 
0.1%
2016-01-18 65
 
0.1%
2015-07-29 64
 
0.1%
2016-05-16 62
 
0.1%
Other values (3041) 58268
98.5%

Most occurring characters

ValueCountFrequency (%)
0 134500
22.7%
- 118274
20.0%
1 112255
19.0%
2 98883
16.7%
5 23416
 
4.0%
3 22127
 
3.7%
6 22023
 
3.7%
4 21461
 
3.6%
7 15710
 
2.7%
8 11415
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 473096
80.0%
Dash Punctuation 118274
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 134500
28.4%
1 112255
23.7%
2 98883
20.9%
5 23416
 
4.9%
3 22127
 
4.7%
6 22023
 
4.7%
4 21461
 
4.5%
7 15710
 
3.3%
8 11415
 
2.4%
9 11306
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 118274
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 591370
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 134500
22.7%
- 118274
20.0%
1 112255
19.0%
2 98883
16.7%
5 23416
 
4.0%
3 22127
 
3.7%
6 22023
 
3.7%
4 21461
 
3.6%
7 15710
 
2.7%
8 11415
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 591370
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 134500
22.7%
- 118274
20.0%
1 112255
19.0%
2 98883
16.7%
5 23416
 
4.0%
3 22127
 
3.7%
6 22023
 
3.7%
4 21461
 
3.6%
7 15710
 
2.7%
8 11415
 
1.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size58.0 KiB
False
43713 
True
15575 
ValueCountFrequency (%)
False 43713
73.7%
True 15575
 
26.3%
2023-03-07T01:15:13.512175image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

last_review
Categorical

HIGH CARDINALITY  MISSING 

Distinct1313
Distinct (%)2.8%
Missing12633
Missing (%)21.3%
Memory size463.3 KiB
2017-04-30
 
1101
2017-09-24
 
1047
2017-09-17
 
962
2017-04-23
 
828
2017-09-18
 
668
Other values (1308)
42049 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters466550
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique270 ?
Unique (%)0.6%

Sample

1st row2017-09-24
2nd row2016-07-24
3rd row2017-08-01
4th row2017-03-29
5th row2017-03-19

Common Values

ValueCountFrequency (%)
2017-04-30 1101
 
1.9%
2017-09-24 1047
 
1.8%
2017-09-17 962
 
1.6%
2017-04-23 828
 
1.4%
2017-09-18 668
 
1.1%
2017-09-25 657
 
1.1%
2017-04-16 581
 
1.0%
2017-10-01 576
 
1.0%
2017-05-07 570
 
1.0%
2017-09-16 559
 
0.9%
Other values (1303) 39106
66.0%
(Missing) 12633
 
21.3%

Length

2023-03-07T01:15:13.693065image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2017-04-30 1101
 
2.4%
2017-09-24 1047
 
2.2%
2017-09-17 962
 
2.1%
2017-04-23 828
 
1.8%
2017-09-18 668
 
1.4%
2017-09-25 657
 
1.4%
2017-04-16 581
 
1.2%
2017-10-01 576
 
1.2%
2017-05-07 570
 
1.2%
2017-09-16 559
 
1.2%
Other values (1303) 39106
83.8%

Most occurring characters

ValueCountFrequency (%)
0 108291
23.2%
- 93310
20.0%
1 74640
16.0%
2 70268
15.1%
7 43211
 
9.3%
9 17992
 
3.9%
4 15012
 
3.2%
6 13883
 
3.0%
3 10500
 
2.3%
5 10363
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 373240
80.0%
Dash Punctuation 93310
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 108291
29.0%
1 74640
20.0%
2 70268
18.8%
7 43211
 
11.6%
9 17992
 
4.8%
4 15012
 
4.0%
6 13883
 
3.7%
3 10500
 
2.8%
5 10363
 
2.8%
8 9080
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 93310
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 466550
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 108291
23.2%
- 93310
20.0%
1 74640
16.0%
2 70268
15.1%
7 43211
 
9.3%
9 17992
 
3.9%
4 15012
 
3.2%
6 13883
 
3.0%
3 10500
 
2.3%
5 10363
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 466550
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 108291
23.2%
- 93310
20.0%
1 74640
16.0%
2 70268
15.1%
7 43211
 
9.3%
9 17992
 
3.9%
4 15012
 
3.2%
6 13883
 
3.0%
3 10500
 
2.3%
5 10363
 
2.2%

latitude
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct59288
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.444483
Minimum33.339007
Maximum42.390437
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size463.3 KiB
2023-03-07T01:15:13.953278image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum33.339007
5-th percentile33.989561
Q134.127927
median40.662198
Q340.745835
95-th percentile41.978593
Maximum42.390437
Range9.0514305
Interquartile range (IQR)6.6179088

Descriptive statistics

Standard deviation3.0798885
Coefficient of variation (CV)0.080112626
Kurtosis-1.4148773
Mean38.444483
Median Absolute Deviation (MAD)1.6680485
Skewness-0.53459853
Sum2279296.5
Variance9.4857131
MonotonicityNot monotonic
2023-03-07T01:15:14.238475image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40.65035957 1
 
< 0.1%
34.08207018 1
 
< 0.1%
33.88080461 1
 
< 0.1%
40.84367706 1
 
< 0.1%
42.36638188 1
 
< 0.1%
41.8810544 1
 
< 0.1%
34.02692472 1
 
< 0.1%
34.14162445 1
 
< 0.1%
34.12879066 1
 
< 0.1%
40.68859221 1
 
< 0.1%
Other values (59278) 59278
> 99.9%
ValueCountFrequency (%)
33.33900666 1
< 0.1%
33.3393274 1
< 0.1%
33.34052097 1
< 0.1%
33.34091632 1
< 0.1%
33.34301097 1
< 0.1%
33.34328706 1
< 0.1%
33.34357368 1
< 0.1%
33.34362433 1
< 0.1%
33.34514753 1
< 0.1%
33.35237284 1
< 0.1%
ValueCountFrequency (%)
42.39043718 1
< 0.1%
42.39024754 1
< 0.1%
42.38990669 1
< 0.1%
42.38982827 1
< 0.1%
42.38978814 1
< 0.1%
42.38977245 1
< 0.1%
42.38968173 1
< 0.1%
42.38965277 1
< 0.1%
42.38953063 1
< 0.1%
42.38903148 1
< 0.1%

longitude
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct59288
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-92.40902
Minimum-122.5115
Maximum-70.989359
Zeros0
Zeros (%)0.0%
Negative59288
Negative (%)100.0%
Memory size463.3 KiB
2023-03-07T01:15:14.512199image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum-122.5115
5-th percentile-122.4229
Q1-118.34219
median-76.998126
Q3-73.954732
95-th percentile-73.787438
Maximum-70.989359
Range51.522141
Interquartile range (IQR)44.387461

Descriptive statistics

Standard deviation21.698695
Coefficient of variation (CV)-0.23481144
Kurtosis-1.7736241
Mean-92.40902
Median Absolute Deviation (MAD)3.1463814
Skewness-0.40647297
Sum-5478746
Variance470.83336
MonotonicityNot monotonic
2023-03-07T01:15:14.810973image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-74.00357406 1
 
< 0.1%
-118.309648 1
 
< 0.1%
-118.3688065 1
 
< 0.1%
-73.93751495 1
 
< 0.1%
-71.05587868 1
 
< 0.1%
-87.65741676 1
 
< 0.1%
-117.8053239 1
 
< 0.1%
-118.1520552 1
 
< 0.1%
-117.9175587 1
 
< 0.1%
-73.97289592 1
 
< 0.1%
Other values (59278) 59278
> 99.9%
ValueCountFrequency (%)
-122.5115 1
< 0.1%
-122.5109053 1
< 0.1%
-122.5096352 1
< 0.1%
-122.5093674 1
< 0.1%
-122.5093648 1
< 0.1%
-122.5093356 1
< 0.1%
-122.5092505 1
< 0.1%
-122.50916 1
< 0.1%
-122.5091375 1
< 0.1%
-122.5090638 1
< 0.1%
ValueCountFrequency (%)
-70.98935853 1
< 0.1%
-70.99186148 1
< 0.1%
-71.00026054 1
< 0.1%
-71.00046159 1
< 0.1%
-71.00154803 1
< 0.1%
-71.00176944 1
< 0.1%
-71.00471442 1
< 0.1%
-71.0051918 1
< 0.1%
-71.00574429 1
< 0.1%
-71.00585743 1
< 0.1%

name
Categorical

HIGH CARDINALITY  UNIFORM 

Distinct58782
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size463.3 KiB
East Village Studio
 
5
Location, Location, Location
 
5
Bunk bed in the Treat Street Clubhouse
 
5
Your home away from home
 
5
Cozy Private Room
 
5
Other values (58777)
59263 

Length

Max length179
Median length67
Mean length34.825884
Min length1

Characters and Unicode

Total characters2064757
Distinct characters1094
Distinct categories22 ?
Distinct scripts12 ?
Distinct blocks19 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58356 ?
Unique (%)98.4%

Sample

1st rowAFFORDABLE & COZY IN SUNSET PARK T
2nd rowLuxurious and quiet - 30 second walk to the beach!
3rd rowBensonhurst STYLISH STUDIO
4th rowLA San Gabriel Suit room 圣盖博大套房 免费停车 Free Parking
5th rowXTRA Large 2bdrm 2bath in the City near "El" Train

Common Values

ValueCountFrequency (%)
East Village Studio 5
 
< 0.1%
Location, Location, Location 5
 
< 0.1%
Bunk bed in the Treat Street Clubhouse 5
 
< 0.1%
Your home away from home 5
 
< 0.1%
Cozy Private Room 5
 
< 0.1%
Spacious Brooklyn Apartment 5
 
< 0.1%
The Treehouse 4
 
< 0.1%
Cozy apartment in Brooklyn 4
 
< 0.1%
Home 4
 
< 0.1%
Studio 4
 
< 0.1%
Other values (58772) 59242
99.9%

Length

2023-03-07T01:15:15.153639image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
in 17791
 
5.2%
room 9998
 
2.9%
8940
 
2.6%
private 8296
 
2.4%
bedroom 7225
 
2.1%
apartment 5852
 
1.7%
cozy 4988
 
1.5%
the 4980
 
1.5%
apt 4596
 
1.3%
studio 4225
 
1.2%
Other values (15971) 264258
77.5%

Most occurring characters

ValueCountFrequency (%)
283850
 
13.7%
e 149660
 
7.2%
o 146181
 
7.1%
a 118131
 
5.7%
t 116960
 
5.7%
i 108579
 
5.3%
n 104902
 
5.1%
r 104752
 
5.1%
l 62370
 
3.0%
s 55151
 
2.7%
Other values (1084) 814221
39.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1373982
66.5%
Uppercase Letter 315304
 
15.3%
Space Separator 283855
 
13.7%
Other Punctuation 41970
 
2.0%
Decimal Number 28138
 
1.4%
Dash Punctuation 8063
 
0.4%
Other Letter 7461
 
0.4%
Math Symbol 2055
 
0.1%
Close Punctuation 1627
 
0.1%
Open Punctuation 1449
 
0.1%
Other values (12) 853
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
320
 
4.3%
120
 
1.6%
120
 
1.6%
117
 
1.6%
98
 
1.3%
94
 
1.3%
93
 
1.2%
90
 
1.2%
89
 
1.2%
88
 
1.2%
Other values (858) 6232
83.5%
Lowercase Letter
ValueCountFrequency (%)
e 149660
10.9%
o 146181
10.6%
a 118131
 
8.6%
t 116960
 
8.5%
i 108579
 
7.9%
n 104902
 
7.6%
r 104752
 
7.6%
l 62370
 
4.5%
s 55151
 
4.0%
u 50735
 
3.7%
Other values (69) 356561
26.0%
Uppercase Letter
ValueCountFrequency (%)
B 33504
 
10.6%
S 28709
 
9.1%
C 26281
 
8.3%
A 23045
 
7.3%
R 19884
 
6.3%
L 18934
 
6.0%
P 18178
 
5.8%
H 17878
 
5.7%
E 14986
 
4.8%
M 12890
 
4.1%
Other values (29) 101015
32.0%
Other Symbol
ValueCountFrequency (%)
180
41.6%
101
23.3%
58
 
13.4%
12
 
2.8%
9
 
2.1%
9
 
2.1%
8
 
1.8%
6
 
1.4%
5
 
1.2%
° 5
 
1.2%
Other values (18) 40
 
9.2%
Other Punctuation
ValueCountFrequency (%)
, 10394
24.8%
! 9695
23.1%
/ 7823
18.6%
. 5114
12.2%
& 4013
 
9.6%
' 1393
 
3.3%
* 869
 
2.1%
: 792
 
1.9%
# 632
 
1.5%
" 419
 
1.0%
Other values (15) 826
 
2.0%
Decimal Number
ValueCountFrequency (%)
1 9498
33.8%
2 8417
29.9%
3 2898
 
10.3%
0 2096
 
7.4%
5 1827
 
6.5%
4 1439
 
5.1%
6 558
 
2.0%
9 518
 
1.8%
8 449
 
1.6%
7 438
 
1.6%
Math Symbol
ValueCountFrequency (%)
+ 1563
76.1%
| 258
 
12.6%
~ 179
 
8.7%
> 25
 
1.2%
= 18
 
0.9%
< 8
 
0.4%
3
 
0.1%
÷ 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 1484
91.2%
] 92
 
5.7%
24
 
1.5%
12
 
0.7%
} 12
 
0.7%
2
 
0.1%
1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 1301
89.8%
[ 94
 
6.5%
27
 
1.9%
12
 
0.8%
{ 12
 
0.8%
2
 
0.1%
1
 
0.1%
Nonspacing Mark
ValueCountFrequency (%)
104
87.4%
5
 
4.2%
5
 
4.2%
5
 
4.2%
Space Separator
ValueCountFrequency (%)
283850
> 99.9%
  3
 
< 0.1%
  2
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 8005
99.3%
32
 
0.4%
26
 
0.3%
Modifier Symbol
ValueCountFrequency (%)
^ 18
81.8%
` 4
 
18.2%
Final Punctuation
ValueCountFrequency (%)
14
73.7%
5
 
26.3%
Other Number
ValueCountFrequency (%)
² 6
75.0%
½ 2
 
25.0%
Currency Symbol
ValueCountFrequency (%)
$ 179
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 57
100.0%
Initial Punctuation
ValueCountFrequency (%)
5
100.0%
Spacing Mark
ValueCountFrequency (%)
5
100.0%
Modifier Letter
ValueCountFrequency (%)
4
100.0%
Enclosing Mark
ValueCountFrequency (%)
1
100.0%
Format
ValueCountFrequency (%)
­ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1689209
81.8%
Common 367885
 
17.8%
Han 7229
 
0.4%
Inherited 110
 
< 0.1%
Cyrillic 78
 
< 0.1%
Hangul 68
 
< 0.1%
Katakana 46
 
< 0.1%
Devanagari 42
 
< 0.1%
Arabic 30
 
< 0.1%
Hiragana 30
 
< 0.1%
Other values (2) 30
 
< 0.1%

Most frequent character per script

Han
ValueCountFrequency (%)
320
 
4.4%
120
 
1.7%
120
 
1.7%
117
 
1.6%
98
 
1.4%
94
 
1.3%
93
 
1.3%
90
 
1.2%
89
 
1.2%
88
 
1.2%
Other values (738) 6000
83.0%
Common
ValueCountFrequency (%)
283850
77.2%
, 10394
 
2.8%
! 9695
 
2.6%
1 9498
 
2.6%
2 8417
 
2.3%
- 8005
 
2.2%
/ 7823
 
2.1%
. 5114
 
1.4%
& 4013
 
1.1%
3 2898
 
0.8%
Other values (92) 18178
 
4.9%
Latin
ValueCountFrequency (%)
e 149660
 
8.9%
o 146181
 
8.7%
a 118131
 
7.0%
t 116960
 
6.9%
i 108579
 
6.4%
n 104902
 
6.2%
r 104752
 
6.2%
l 62370
 
3.7%
s 55151
 
3.3%
u 50735
 
3.0%
Other values (80) 671788
39.8%
Hangul
ValueCountFrequency (%)
4
 
5.9%
3
 
4.4%
3
 
4.4%
3
 
4.4%
2
 
2.9%
2
 
2.9%
2
 
2.9%
2
 
2.9%
2
 
2.9%
2
 
2.9%
Other values (38) 43
63.2%
Cyrillic
ValueCountFrequency (%)
о 7
 
9.0%
р 7
 
9.0%
е 6
 
7.7%
с 5
 
6.4%
н 5
 
6.4%
к 4
 
5.1%
л 4
 
5.1%
а 4
 
5.1%
п 3
 
3.8%
у 3
 
3.8%
Other values (19) 30
38.5%
Katakana
ValueCountFrequency (%)
6
 
13.0%
3
 
6.5%
3
 
6.5%
3
 
6.5%
3
 
6.5%
2
 
4.3%
2
 
4.3%
2
 
4.3%
2
 
4.3%
2
 
4.3%
Other values (16) 18
39.1%
Hiragana
ValueCountFrequency (%)
4
13.3%
3
 
10.0%
3
 
10.0%
2
 
6.7%
2
 
6.7%
2
 
6.7%
2
 
6.7%
2
 
6.7%
1
 
3.3%
1
 
3.3%
Other values (8) 8
26.7%
Hebrew
ValueCountFrequency (%)
ו 5
19.2%
י 4
15.4%
ב 3
11.5%
ר 3
11.5%
ה 2
 
7.7%
ל 1
 
3.8%
א 1
 
3.8%
מ 1
 
3.8%
ס 1
 
3.8%
ג 1
 
3.8%
Other values (4) 4
15.4%
Devanagari
ValueCountFrequency (%)
5
11.9%
5
11.9%
5
11.9%
5
11.9%
5
11.9%
5
11.9%
5
11.9%
5
11.9%
2
 
4.8%
Arabic
ValueCountFrequency (%)
ه 5
16.7%
ا 5
16.7%
ب 5
16.7%
ك 5
16.7%
ل 5
16.7%
أ 5
16.7%
Inherited
ValueCountFrequency (%)
104
94.5%
5
 
4.5%
1
 
0.9%
Syriac
ValueCountFrequency (%)
ܓ 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2056006
99.6%
CJK 7229
 
0.4%
None 539
 
< 0.1%
Misc Symbols 278
 
< 0.1%
Dingbats 127
 
< 0.1%
Punctuation 123
 
< 0.1%
VS 109
 
< 0.1%
Cyrillic 78
 
< 0.1%
Hangul 68
 
< 0.1%
Katakana 50
 
< 0.1%
Other values (9) 150
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
283850
 
13.8%
e 149660
 
7.3%
o 146181
 
7.1%
a 118131
 
5.7%
t 116960
 
5.7%
i 108579
 
5.3%
n 104902
 
5.1%
r 104752
 
5.1%
l 62370
 
3.0%
s 55151
 
2.7%
Other values (85) 805470
39.2%
CJK
ValueCountFrequency (%)
320
 
4.4%
120
 
1.7%
120
 
1.7%
117
 
1.6%
98
 
1.4%
94
 
1.3%
93
 
1.3%
90
 
1.2%
89
 
1.2%
88
 
1.2%
Other values (738) 6000
83.0%
None
ValueCountFrequency (%)
223
41.4%
45
 
8.3%
31
 
5.8%
27
 
5.0%
26
 
4.8%
24
 
4.5%
à 17
 
3.2%
12
 
2.2%
12
 
2.2%
ó 12
 
2.2%
Other values (53) 110
20.4%
Misc Symbols
ValueCountFrequency (%)
180
64.7%
58
 
20.9%
12
 
4.3%
9
 
3.2%
9
 
3.2%
5
 
1.8%
2
 
0.7%
1
 
0.4%
1
 
0.4%
1
 
0.4%
VS
ValueCountFrequency (%)
104
95.4%
5
 
4.6%
Dingbats
ValueCountFrequency (%)
101
79.5%
8
 
6.3%
5
 
3.9%
3
 
2.4%
3
 
2.4%
2
 
1.6%
2
 
1.6%
2
 
1.6%
1
 
0.8%
Punctuation
ValueCountFrequency (%)
33
26.8%
32
26.0%
26
21.1%
14
11.4%
6
 
4.9%
5
 
4.1%
5
 
4.1%
2
 
1.6%
Cyrillic
ValueCountFrequency (%)
о 7
 
9.0%
р 7
 
9.0%
е 6
 
7.7%
с 5
 
6.4%
н 5
 
6.4%
к 4
 
5.1%
л 4
 
5.1%
а 4
 
5.1%
п 3
 
3.8%
у 3
 
3.8%
Other values (19) 30
38.5%
Letterlike Symbols
ValueCountFrequency (%)
6
100.0%
Katakana
ValueCountFrequency (%)
6
 
12.0%
4
 
8.0%
3
 
6.0%
3
 
6.0%
3
 
6.0%
3
 
6.0%
2
 
4.0%
2
 
4.0%
2
 
4.0%
2
 
4.0%
Other values (17) 20
40.0%
Arabic
ValueCountFrequency (%)
ه 5
16.7%
ا 5
16.7%
ب 5
16.7%
ك 5
16.7%
ل 5
16.7%
أ 5
16.7%
Devanagari
ValueCountFrequency (%)
5
11.9%
5
11.9%
5
11.9%
5
11.9%
5
11.9%
5
11.9%
5
11.9%
5
11.9%
2
 
4.8%
Hebrew
ValueCountFrequency (%)
ו 5
19.2%
י 4
15.4%
ב 3
11.5%
ר 3
11.5%
ה 2
 
7.7%
ל 1
 
3.8%
א 1
 
3.8%
מ 1
 
3.8%
ס 1
 
3.8%
ג 1
 
3.8%
Other values (4) 4
15.4%
Block Elements
ValueCountFrequency (%)
4
40.0%
2
20.0%
2
20.0%
2
20.0%
Syriac
ValueCountFrequency (%)
ܓ 4
100.0%
Hiragana
ValueCountFrequency (%)
4
13.3%
3
 
10.0%
3
 
10.0%
2
 
6.7%
2
 
6.7%
2
 
6.7%
2
 
6.7%
2
 
6.7%
1
 
3.3%
1
 
3.3%
Other values (8) 8
26.7%
Hangul
ValueCountFrequency (%)
4
 
5.9%
3
 
4.4%
3
 
4.4%
3
 
4.4%
2
 
2.9%
2
 
2.9%
2
 
2.9%
2
 
2.9%
2
 
2.9%
2
 
2.9%
Other values (38) 43
63.2%
Geometric Shapes
ValueCountFrequency (%)
1
100.0%
Misc Technical
ValueCountFrequency (%)
1
100.0%

neighbourhood
Categorical

HIGH CARDINALITY  MISSING 

Distinct610
Distinct (%)1.1%
Missing5513
Missing (%)9.3%
Memory size463.3 KiB
Williamsburg
 
2298
Bedford-Stuyvesant
 
1741
Bushwick
 
1280
Upper West Side
 
1120
Mid-Wilshire
 
1110
Other values (605)
46226 

Length

Max length35
Median length28
Mean length11.857852
Min length4

Characters and Unicode

Total characters637656
Distinct characters58
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)0.1%

Sample

1st rowSunset Park
2nd rowVenice
3rd rowBensonhurst
4th rowSan Gabriel
5th rowWoodlawn

Common Values

ValueCountFrequency (%)
Williamsburg 2298
 
3.9%
Bedford-Stuyvesant 1741
 
2.9%
Bushwick 1280
 
2.2%
Upper West Side 1120
 
1.9%
Mid-Wilshire 1110
 
1.9%
Harlem 1099
 
1.9%
Hollywood 1045
 
1.8%
Hell's Kitchen 1044
 
1.8%
Venice 993
 
1.7%
Upper East Side 956
 
1.6%
Other values (600) 41089
69.3%
(Missing) 5513
 
9.3%

Length

2023-03-07T01:15:15.478249image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
east 3874
 
4.3%
heights 3642
 
4.0%
west 2967
 
3.3%
side 2789
 
3.1%
park 2580
 
2.8%
hollywood 2384
 
2.6%
williamsburg 2298
 
2.5%
upper 2076
 
2.3%
hill 2050
 
2.3%
bedford-stuyvesant 1741
 
1.9%
Other values (596) 64290
70.9%

Most occurring characters

ValueCountFrequency (%)
e 55070
 
8.6%
i 46440
 
7.3%
a 42665
 
6.7%
t 40010
 
6.3%
o 39832
 
6.2%
l 39394
 
6.2%
36921
 
5.8%
s 35477
 
5.6%
r 35154
 
5.5%
n 31819
 
5.0%
Other values (48) 234874
36.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 496977
77.9%
Uppercase Letter 97308
 
15.3%
Space Separator 36921
 
5.8%
Dash Punctuation 3487
 
0.5%
Other Punctuation 2811
 
0.4%
Decimal Number 152
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 55070
11.1%
i 46440
9.3%
a 42665
 
8.6%
t 40010
 
8.1%
o 39832
 
8.0%
l 39394
 
7.9%
s 35477
 
7.1%
r 35154
 
7.1%
n 31819
 
6.4%
d 19310
 
3.9%
Other values (16) 111806
22.5%
Uppercase Letter
ValueCountFrequency (%)
H 13441
13.8%
S 10326
10.6%
W 8983
 
9.2%
B 7997
 
8.2%
C 7003
 
7.2%
M 5526
 
5.7%
P 5330
 
5.5%
E 5287
 
5.4%
L 4048
 
4.2%
V 3775
 
3.9%
Other values (14) 25592
26.3%
Other Punctuation
ValueCountFrequency (%)
/ 1687
60.0%
' 1076
38.3%
. 37
 
1.3%
, 11
 
0.4%
Decimal Number
ValueCountFrequency (%)
1 76
50.0%
6 76
50.0%
Space Separator
ValueCountFrequency (%)
36921
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3487
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 594285
93.2%
Common 43371
 
6.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 55070
 
9.3%
i 46440
 
7.8%
a 42665
 
7.2%
t 40010
 
6.7%
o 39832
 
6.7%
l 39394
 
6.6%
s 35477
 
6.0%
r 35154
 
5.9%
n 31819
 
5.4%
d 19310
 
3.2%
Other values (40) 209114
35.2%
Common
ValueCountFrequency (%)
36921
85.1%
- 3487
 
8.0%
/ 1687
 
3.9%
' 1076
 
2.5%
1 76
 
0.2%
6 76
 
0.2%
. 37
 
0.1%
, 11
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 637656
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 55070
 
8.6%
i 46440
 
7.3%
a 42665
 
6.7%
t 40010
 
6.3%
o 39832
 
6.2%
l 39394
 
6.2%
36921
 
5.8%
s 35477
 
5.6%
r 35154
 
5.5%
n 31819
 
5.0%
Other values (48) 234874
36.8%

number_of_reviews
Real number (ℝ)

Distinct356
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.894498
Minimum0
Maximum605
Zeros12626
Zeros (%)21.3%
Negative0
Negative (%)0.0%
Memory size463.3 KiB
2023-03-07T01:15:15.753388image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median6
Q323
95-th percentile95
Maximum605
Range605
Interquartile range (IQR)22

Descriptive statistics

Standard deviation37.748916
Coefficient of variation (CV)1.8066438
Kurtosis20.084815
Mean20.894498
Median Absolute Deviation (MAD)6
Skewness3.6685249
Sum1238793
Variance1424.9806
MonotonicityNot monotonic
2023-03-07T01:15:16.038337image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 12626
21.3%
1 5696
 
9.6%
2 3783
 
6.4%
3 2899
 
4.9%
4 2301
 
3.9%
5 2039
 
3.4%
6 1646
 
2.8%
7 1489
 
2.5%
8 1328
 
2.2%
9 1162
 
2.0%
Other values (346) 24319
41.0%
ValueCountFrequency (%)
0 12626
21.3%
1 5696
9.6%
2 3783
 
6.4%
3 2899
 
4.9%
4 2301
 
3.9%
5 2039
 
3.4%
6 1646
 
2.8%
7 1489
 
2.5%
8 1328
 
2.2%
9 1162
 
2.0%
ValueCountFrequency (%)
605 1
< 0.1%
542 1
< 0.1%
530 1
< 0.1%
525 1
< 0.1%
505 1
< 0.1%
495 1
< 0.1%
469 1
< 0.1%
453 1
< 0.1%
451 1
< 0.1%
425 1
< 0.1%

review_scores_rating
Real number (ℝ)

Distinct51
Distinct (%)0.1%
Missing13341
Missing (%)22.5%
Infinite0
Infinite (%)0.0%
Mean94.051407
Minimum20
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size463.3 KiB
2023-03-07T01:15:16.335613image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile80
Q192
median96
Q3100
95-th percentile100
Maximum100
Range80
Interquartile range (IQR)8

Descriptive statistics

Standard deviation7.8848338
Coefficient of variation (CV)0.083835362
Kurtosis19.871876
Mean94.051407
Median Absolute Deviation (MAD)4
Skewness-3.3864263
Sum4321380
Variance62.170604
MonotonicityNot monotonic
2023-03-07T01:15:17.179115image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 12958
21.9%
98 3520
 
5.9%
96 3313
 
5.6%
97 3251
 
5.5%
95 2961
 
5.0%
93 2915
 
4.9%
90 2272
 
3.8%
94 2113
 
3.6%
99 2099
 
3.5%
80 1711
 
2.9%
Other values (41) 8834
14.9%
(Missing) 13341
22.5%
ValueCountFrequency (%)
20 78
0.1%
27 1
 
< 0.1%
30 4
 
< 0.1%
40 78
0.1%
47 4
 
< 0.1%
49 1
 
< 0.1%
50 25
 
< 0.1%
53 7
 
< 0.1%
55 3
 
< 0.1%
56 1
 
< 0.1%
ValueCountFrequency (%)
100 12958
21.9%
99 2099
 
3.5%
98 3520
 
5.9%
97 3251
 
5.5%
96 3313
 
5.6%
95 2961
 
5.0%
94 2113
 
3.6%
93 2915
 
4.9%
92 1661
 
2.8%
91 1285
 
2.2%

thumbnail_url
Categorical

HIGH CARDINALITY  MISSING  UNIFORM 

Distinct52758
Distinct (%)> 99.9%
Missing6520
Missing (%)11.0%
Memory size463.3 KiB
https://a0.muscache.com/im/pictures/109405834/9a555e66_original.jpg?aki_policy=small
 
2
https://a0.muscache.com/im/pictures/104667326/a7a2b145_original.jpg?aki_policy=small
 
2
https://a0.muscache.com/im/pictures/4491e5c5-33f6-4704-9887-76a059f86fda.jpg?aki_policy=small
 
2
https://a0.muscache.com/im/pictures/28563531/1000de61_original.jpg?aki_policy=small
 
2
https://a0.muscache.com/im/pictures/23033013/54d62516_original.jpg?aki_policy=small
 
2
Other values (52753)
52758 

Length

Max length93
Median length93
Mean length90.504757
Min length79

Characters and Unicode

Total characters4775755
Distinct characters38
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52748 ?
Unique (%)> 99.9%

Sample

1st rowhttps://a0.muscache.com/im/pictures/105652616/6eb122d7_original.jpg?aki_policy=small
2nd rowhttps://a0.muscache.com/im/pictures/bf8ee448-b113-46cd-aeed-705825ec52e6.jpg?aki_policy=small
3rd rowhttps://a0.muscache.com/im/pictures/0cff238c-a526-4c07-85d8-1d6522de7892.jpg?aki_policy=small
4th rowhttps://a0.muscache.com/im/pictures/92108903/0b86d70a_original.jpg?aki_policy=small
5th rowhttps://a0.muscache.com/im/pictures/83993776/de87ff9a_original.jpg?aki_policy=small

Common Values

ValueCountFrequency (%)
https://a0.muscache.com/im/pictures/109405834/9a555e66_original.jpg?aki_policy=small 2
 
< 0.1%
https://a0.muscache.com/im/pictures/104667326/a7a2b145_original.jpg?aki_policy=small 2
 
< 0.1%
https://a0.muscache.com/im/pictures/4491e5c5-33f6-4704-9887-76a059f86fda.jpg?aki_policy=small 2
 
< 0.1%
https://a0.muscache.com/im/pictures/28563531/1000de61_original.jpg?aki_policy=small 2
 
< 0.1%
https://a0.muscache.com/im/pictures/23033013/54d62516_original.jpg?aki_policy=small 2
 
< 0.1%
https://a0.muscache.com/im/pictures/105275678/2ec252ae_original.jpg?aki_policy=small 2
 
< 0.1%
https://a0.muscache.com/im/pictures/61042471/5543b0e0_original.jpg?aki_policy=small 2
 
< 0.1%
https://a0.muscache.com/im/pictures/70087089/bc66229a_original.jpg?aki_policy=small 2
 
< 0.1%
https://a0.muscache.com/im/pictures/623a5884-0613-4cbd-962f-bbd28c7f47bc.jpg?aki_policy=small 2
 
< 0.1%
https://a0.muscache.com/im/pictures/39dc7b1a-15ca-4820-ac7d-44325007f1a2.jpg?aki_policy=small 2
 
< 0.1%
Other values (52748) 52748
89.0%
(Missing) 6520
 
11.0%

Length

2023-03-07T01:15:17.694257image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://a0.muscache.com/im/pictures/109405834/9a555e66_original.jpg?aki_policy=small 2
 
< 0.1%
https://a0.muscache.com/im/pictures/4491e5c5-33f6-4704-9887-76a059f86fda.jpg?aki_policy=small 2
 
< 0.1%
https://a0.muscache.com/im/pictures/28563531/1000de61_original.jpg?aki_policy=small 2
 
< 0.1%
https://a0.muscache.com/im/pictures/23033013/54d62516_original.jpg?aki_policy=small 2
 
< 0.1%
https://a0.muscache.com/im/pictures/105275678/2ec252ae_original.jpg?aki_policy=small 2
 
< 0.1%
https://a0.muscache.com/im/pictures/61042471/5543b0e0_original.jpg?aki_policy=small 2
 
< 0.1%
https://a0.muscache.com/im/pictures/70087089/bc66229a_original.jpg?aki_policy=small 2
 
< 0.1%
https://a0.muscache.com/im/pictures/623a5884-0613-4cbd-962f-bbd28c7f47bc.jpg?aki_policy=small 2
 
< 0.1%
https://a0.muscache.com/im/pictures/39dc7b1a-15ca-4820-ac7d-44325007f1a2.jpg?aki_policy=small 2
 
< 0.1%
https://a0.muscache.com/im/pictures/104667326/a7a2b145_original.jpg?aki_policy=small 2
 
< 0.1%
Other values (52748) 52748
> 99.9%

Most occurring characters

ValueCountFrequency (%)
c 344873
 
7.2%
a 314611
 
6.6%
/ 277074
 
5.8%
i 237540
 
5.0%
m 211072
 
4.4%
p 211072
 
4.4%
s 211072
 
4.4%
e 186173
 
3.9%
l 171538
 
3.6%
. 158304
 
3.3%
Other values (28) 2452426
51.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2932757
61.4%
Decimal Number 1025178
 
21.5%
Other Punctuation 540914
 
11.3%
Dash Punctuation 158136
 
3.3%
Connector Punctuation 66002
 
1.4%
Math Symbol 52768
 
1.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
c 344873
11.8%
a 314611
10.7%
i 237540
 
8.1%
m 211072
 
7.2%
p 211072
 
7.2%
s 211072
 
7.2%
e 186173
 
6.3%
l 171538
 
5.8%
t 158304
 
5.4%
o 118770
 
4.0%
Other values (11) 767732
26.2%
Decimal Number
ValueCountFrequency (%)
0 144979
14.1%
4 130395
12.7%
9 100862
9.8%
8 100752
9.8%
1 92971
9.1%
7 91567
8.9%
6 91252
8.9%
5 91105
8.9%
2 90664
8.8%
3 90631
8.8%
Other Punctuation
ValueCountFrequency (%)
/ 277074
51.2%
. 158304
29.3%
? 52768
 
9.8%
: 52768
 
9.8%
Dash Punctuation
ValueCountFrequency (%)
- 158136
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 66002
100.0%
Math Symbol
ValueCountFrequency (%)
= 52768
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2932757
61.4%
Common 1842998
38.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
c 344873
11.8%
a 314611
10.7%
i 237540
 
8.1%
m 211072
 
7.2%
p 211072
 
7.2%
s 211072
 
7.2%
e 186173
 
6.3%
l 171538
 
5.8%
t 158304
 
5.4%
o 118770
 
4.0%
Other values (11) 767732
26.2%
Common
ValueCountFrequency (%)
/ 277074
15.0%
. 158304
 
8.6%
- 158136
 
8.6%
0 144979
 
7.9%
4 130395
 
7.1%
9 100862
 
5.5%
8 100752
 
5.5%
1 92971
 
5.0%
7 91567
 
5.0%
6 91252
 
5.0%
Other values (7) 496706
27.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4775755
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
c 344873
 
7.2%
a 314611
 
6.6%
/ 277074
 
5.8%
i 237540
 
5.0%
m 211072
 
4.4%
p 211072
 
4.4%
s 211072
 
4.4%
e 186173
 
3.9%
l 171538
 
3.6%
. 158304
 
3.3%
Other values (28) 2452426
51.4%

zipcode
Categorical

HIGH CARDINALITY  MISSING 

Distinct747
Distinct (%)1.3%
Missing789
Missing (%)1.3%
Memory size463.3 KiB
11211.0
 
1090
90291
 
1028
11221
 
945
94110
 
770
90046
 
754
Other values (742)
53912 

Length

Max length10
Median length5
Mean length5.2440555
Min length1

Characters and Unicode

Total characters306772
Distinct characters18
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique90 ?
Unique (%)0.2%

Sample

1st row11232
2nd row90291
3rd row11214
4th row91776
5th row60637

Common Values

ValueCountFrequency (%)
11211.0 1090
 
1.8%
90291 1028
 
1.7%
11221 945
 
1.6%
94110 770
 
1.3%
90046 754
 
1.3%
20002 752
 
1.3%
20009 735
 
1.2%
20001 661
 
1.1%
90028 626
 
1.1%
10019 608
 
1.0%
Other values (737) 50530
85.2%
(Missing) 789
 
1.3%

Length

2023-03-07T01:15:18.102819image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
11211.0 1090
 
1.9%
90291 1028
 
1.8%
11221 945
 
1.6%
94110 770
 
1.3%
90046 754
 
1.3%
20002 752
 
1.3%
20009 735
 
1.3%
20001 661
 
1.1%
90028 626
 
1.1%
10019 608
 
1.0%
Other values (736) 50529
86.4%

Most occurring characters

ValueCountFrequency (%)
0 87177
28.4%
1 74519
24.3%
2 38353
12.5%
9 29840
 
9.7%
6 17040
 
5.6%
3 15342
 
5.0%
4 15035
 
4.9%
5 8135
 
2.7%
7 7762
 
2.5%
. 7116
 
2.3%
Other values (8) 6453
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 299637
97.7%
Other Punctuation 7116
 
2.3%
Dash Punctuation 11
 
< 0.1%
Lowercase Letter 4
 
< 0.1%
Space Separator 3
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 87177
29.1%
1 74519
24.9%
2 38353
12.8%
9 29840
 
10.0%
6 17040
 
5.7%
3 15342
 
5.1%
4 15035
 
5.0%
5 8135
 
2.7%
7 7762
 
2.6%
8 6434
 
2.1%
Lowercase Letter
ValueCountFrequency (%)
e 1
25.0%
a 1
25.0%
r 1
25.0%
m 1
25.0%
Other Punctuation
ValueCountFrequency (%)
. 7116
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Uppercase Letter
ValueCountFrequency (%)
N 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 306767
> 99.9%
Latin 5
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 87177
28.4%
1 74519
24.3%
2 38353
12.5%
9 29840
 
9.7%
6 17040
 
5.6%
3 15342
 
5.0%
4 15035
 
4.9%
5 8135
 
2.7%
7 7762
 
2.5%
. 7116
 
2.3%
Other values (3) 6448
 
2.1%
Latin
ValueCountFrequency (%)
N 1
20.0%
e 1
20.0%
a 1
20.0%
r 1
20.0%
m 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 306772
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 87177
28.4%
1 74519
24.3%
2 38353
12.5%
9 29840
 
9.7%
6 17040
 
5.6%
3 15342
 
5.0%
4 15035
 
4.9%
5 8135
 
2.7%
7 7762
 
2.5%
. 7116
 
2.3%
Other values (8) 6453
 
2.1%

bedrooms
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct11
Distinct (%)< 0.1%
Missing71
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean1.2649577
Minimum0
Maximum10
Zeros5428
Zeros (%)9.2%
Negative0
Negative (%)0.0%
Memory size463.3 KiB
2023-03-07T01:15:18.408212image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile3
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.85175897
Coefficient of variation (CV)0.67334977
Kurtosis7.5255385
Mean1.2649577
Median Absolute Deviation (MAD)0
Skewness1.97557
Sum74907
Variance0.72549334
MonotonicityNot monotonic
2023-03-07T01:15:18.698658image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 39731
67.0%
2 9149
 
15.4%
0 5428
 
9.2%
3 3414
 
5.8%
4 1076
 
1.8%
5 284
 
0.5%
6 81
 
0.1%
7 30
 
0.1%
8 8
 
< 0.1%
10 8
 
< 0.1%
(Missing) 71
 
0.1%
ValueCountFrequency (%)
0 5428
 
9.2%
1 39731
67.0%
2 9149
 
15.4%
3 3414
 
5.8%
4 1076
 
1.8%
5 284
 
0.5%
6 81
 
0.1%
7 30
 
0.1%
8 8
 
< 0.1%
9 8
 
< 0.1%
ValueCountFrequency (%)
10 8
 
< 0.1%
9 8
 
< 0.1%
8 8
 
< 0.1%
7 30
 
0.1%
6 81
 
0.1%
5 284
 
0.5%
4 1076
 
1.8%
3 3414
 
5.8%
2 9149
 
15.4%
1 39731
67.0%

beds
Real number (ℝ)

Distinct18
Distinct (%)< 0.1%
Missing106
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean1.7108073
Minimum0
Maximum18
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size463.3 KiB
2023-03-07T01:15:18.973160image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q32
95-th percentile4
Maximum18
Range18
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.2525466
Coefficient of variation (CV)0.73213771
Kurtosis19.892921
Mean1.7108073
Median Absolute Deviation (MAD)0
Skewness3.3666572
Sum101249
Variance1.5688729
MonotonicityNot monotonic
2023-03-07T01:15:19.358521image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
1 36075
60.8%
2 13419
 
22.6%
3 5129
 
8.7%
4 2465
 
4.2%
5 1037
 
1.7%
6 528
 
0.9%
7 170
 
0.3%
8 141
 
0.2%
10 70
 
0.1%
9 53
 
0.1%
Other values (8) 95
 
0.2%
(Missing) 106
 
0.2%
ValueCountFrequency (%)
0 3
 
< 0.1%
1 36075
60.8%
2 13419
 
22.6%
3 5129
 
8.7%
4 2465
 
4.2%
5 1037
 
1.7%
6 528
 
0.9%
7 170
 
0.3%
8 141
 
0.2%
9 53
 
0.1%
ValueCountFrequency (%)
18 1
 
< 0.1%
16 29
 
< 0.1%
15 6
 
< 0.1%
14 4
 
< 0.1%
13 8
 
< 0.1%
12 25
 
< 0.1%
11 19
 
< 0.1%
10 70
0.1%
9 53
 
0.1%
8 141
0.2%

price
Real number (ℝ)

Distinct716
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean159.95879
Minimum5
Maximum1999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size463.3 KiB
2023-03-07T01:15:19.750935image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile40
Q175
median110
Q3185
95-th percentile425
Maximum1999
Range1994
Interquartile range (IQR)110

Descriptive statistics

Standard deviation168.1933
Coefficient of variation (CV)1.0514789
Kurtosis26.948002
Mean159.95879
Median Absolute Deviation (MAD)45
Skewness4.3319972
Sum9483637
Variance28288.986
MonotonicityNot monotonic
2023-03-07T01:15:20.237820image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
150 2178
 
3.7%
100 2171
 
3.7%
75 1620
 
2.7%
50 1543
 
2.6%
200 1531
 
2.6%
60 1456
 
2.5%
125 1389
 
2.3%
80 1383
 
2.3%
70 1306
 
2.2%
65 1299
 
2.2%
Other values (706) 43412
73.2%
ValueCountFrequency (%)
5 1
 
< 0.1%
10 25
< 0.1%
11 1
 
< 0.1%
12 4
 
< 0.1%
13 1
 
< 0.1%
15 46
0.1%
16 8
 
< 0.1%
17 6
 
< 0.1%
18 11
 
< 0.1%
19 20
< 0.1%
ValueCountFrequency (%)
1999 3
< 0.1%
1995 4
< 0.1%
1980 1
 
< 0.1%
1975 1
 
< 0.1%
1950 6
< 0.1%
1938 1
 
< 0.1%
1900 4
< 0.1%
1895 1
 
< 0.1%
1889 1
 
< 0.1%
1875 1
 
< 0.1%

Interactions

2023-03-07T01:14:59.940677image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:23.520944image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:27.571813image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:34.077820image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:38.697850image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:43.486139image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:48.709366image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:52.332156image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:54.930944image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:57.412779image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:15:00.218194image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:23.816415image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:28.019254image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:34.488360image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:39.139135image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:43.916781image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:49.089583image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:52.592311image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:55.190392image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:57.660653image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:15:00.469890image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:24.125425image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:28.454864image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:34.917144image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:39.620858image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:44.485090image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:49.503451image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:52.847102image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:55.438717image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:57.914432image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:15:00.735894image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:24.482140image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:28.933289image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:35.399572image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:40.159473image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:45.123997image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:49.917830image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:53.129446image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:55.686592image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:58.184298image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:15:00.974977image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:24.873590image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:29.390620image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:35.756454image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:40.506719image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:45.779803image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:50.616420image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:53.371348image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:55.908312image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:58.433061image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:15:01.326792image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:25.271863image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:29.845236image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:36.260238image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:40.961720image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:46.544242image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:51.021283image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:53.618515image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:56.156427image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:58.673116image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:15:01.693528image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:25.694827image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:30.336435image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:36.771642image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:41.409513image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:47.137794image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:51.305647image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:53.864050image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:56.407186image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:58.914088image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:15:02.098697image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:26.187284image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:30.931905image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:37.192906image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:41.924358image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:47.550172image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:51.565179image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:54.140926image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:56.658076image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:59.183765image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:15:02.881335image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:26.618228image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:32.716074image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:37.766796image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:42.312829image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:47.920579image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:51.801884image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:54.392283image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:56.889958image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:59.428739image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:15:03.247834image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:27.113415image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:33.536794image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:38.273532image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:42.755519image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:48.305335image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:52.071960image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:54.666794image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:57.154637image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-03-07T01:14:59.682575image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Correlations

2023-03-07T01:15:20.672003image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
idaccommodatesbathroomslatitudelongitudenumber_of_reviewsreview_scores_ratingbedroomsbedspriceproperty_typeroom_typebed_typecancellation_policycleaning_feecityhost_has_profile_pichost_identity_verifiedhost_response_rateinstant_bookable
id1.0000.004-0.0020.0040.0010.000-0.0060.001-0.001-0.0020.0000.0000.0000.0000.0090.0000.0060.0060.0000.000
accommodates0.0041.0000.368-0.061-0.1030.127-0.0530.5800.7820.5860.0840.4000.0480.1100.1960.0710.0170.0560.0390.061
bathrooms-0.0020.3681.000-0.113-0.124-0.0320.0220.4910.4140.2820.1410.1400.0280.0610.0770.0840.0000.0260.0400.025
latitude0.004-0.061-0.1131.0000.7430.005-0.042-0.046-0.0640.0040.1880.0930.0130.0490.0880.8940.0000.0670.0770.051
longitude0.001-0.103-0.1240.7431.000-0.030-0.066-0.066-0.087-0.1620.2380.0780.0110.0460.0761.0000.0000.0860.0880.030
number_of_reviews0.0000.127-0.0320.005-0.0301.000-0.258-0.0070.085-0.0330.0660.0260.0000.0770.0800.0370.0040.1220.0170.069
review_scores_rating-0.006-0.0530.022-0.042-0.066-0.2581.0000.010-0.0520.0820.0460.0440.0000.0600.0660.0390.0180.0750.0890.084
bedrooms0.0010.5800.491-0.046-0.066-0.0070.0101.0000.6400.4070.0960.3110.0360.0790.1420.0610.0100.0280.0340.020
beds-0.0010.7820.414-0.064-0.0870.085-0.0520.6401.0000.4790.1010.3310.0450.0970.1680.0550.0070.0420.0410.052
price-0.0020.5860.2820.004-0.162-0.0330.0820.4070.4791.0000.0680.2570.0290.0910.0780.0820.0140.0330.0330.023
property_type0.0000.0840.1410.1880.2380.0660.0460.0960.1010.0681.0000.1690.0380.0570.0860.2030.0000.0440.0360.056
room_type0.0000.4000.1400.0930.0780.0260.0440.3110.3310.2570.1691.0000.1870.1320.2150.0900.0000.0700.0890.027
bed_type0.0000.0480.0280.0130.0110.0000.0000.0360.0450.0290.0380.1871.0000.0220.0340.0120.0030.0160.0110.030
cancellation_policy0.0000.1100.0610.0490.0460.0770.0600.0790.0970.0910.0570.1320.0221.0000.3600.0520.0330.1760.3040.023
cleaning_fee0.0090.1960.0770.0880.0760.0800.0660.1420.1680.0780.0860.2150.0340.3601.0000.0830.0220.1590.1320.010
city0.0000.0710.0840.8941.0000.0370.0390.0610.0550.0820.2030.0900.0120.0520.0831.0000.0000.0870.0900.054
host_has_profile_pic0.0060.0170.0000.0000.0000.0040.0180.0100.0070.0140.0000.0000.0030.0330.0220.0001.0000.0750.0790.007
host_identity_verified0.0060.0560.0260.0670.0860.1220.0750.0280.0420.0330.0440.0700.0160.1760.1590.0870.0751.0000.0990.089
host_response_rate0.0000.0390.0400.0770.0880.0170.0890.0340.0410.0330.0360.0890.0110.3040.1320.0900.0790.0991.0000.132
instant_bookable0.0000.0610.0250.0510.0300.0690.0840.0200.0520.0230.0560.0270.0300.0230.0100.0540.0070.0890.1321.000

Missing values

2023-03-07T01:15:04.052453image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
A simple visualization of nullity by column.
2023-03-07T01:15:05.866813image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-03-07T01:15:07.119725image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

idproperty_typeroom_typeamenitiesaccommodatesbathroomsbed_typecancellation_policycleaning_feecitydescriptionfirst_reviewhost_has_profile_pichost_identity_verifiedhost_response_ratehost_sinceinstant_bookablelast_reviewlatitudelongitudenameneighbourhoodnumber_of_reviewsreview_scores_ratingthumbnail_urlzipcodebedroomsbedsprice
046459HousePrivate room{"Wireless Internet","Air conditioning",Kitchen,Heating,"Family/kid friendly","Smoke detector","Carbon monoxide detector","First aid kit","Safety card","Fire extinguisher",Essentials}20.0000Real BedstrictTrueNYCThis is a comfortable, simple beautiful room, one block away from Sunset Park. Clean, cozy and furnished for the comfort of our guests. This is a comfortable a very simple beautiful room one block away from Sunset Park. Clean, cozy and furnished to be a comfortable as possible for our guests. We are centrally located between both 5th and 6th Avenue shops, restaurants, cafes and markets. Sightseeing nearby, include Prospect Park, Brooklyn Museum, Brooklyn Botanical Gardens, Brooklyn Academy of Music, which are all easily commutable via train or cab. We are just 5 blocks away from the D, N, M and R train. Manhattan within 15 minutes or Midtown in 20 minutes. WE PROVIDE: Full side bed with sheets and towel provide. HDTV, WIFI and a warm welcome! You will have full access to the kitchen with microwave, fridge, two burner portable stove, coffee maker, toaster and all cooking ware. and if the weather is behaving good feel free to use our wonderful backyard. Check-in is at 3pm Check-out is a2015-09-24tt100%2011-09-19f2017-09-2440.6504-74.0036AFFORDABLE & COZY IN SUNSET PARK TSunset Park1589.0000https://a0.muscache.com/im/pictures/105652616/6eb122d7_original.jpg?aki_policy=small112321.00001.000050.0000
116468ApartmentEntire home/apt{Internet,"Wireless Internet",Kitchen,Heating,"Smoke detector","Carbon monoxide detector","Fire extinguisher","Lock on bedroom door","translation missing: en.hosting_amenity_49","translation missing: en.hosting_amenity_50"}21.0000Real BedstrictTrueLARenovated clean & modern 1 bedroom in the heart of Venice Beach. Located on a quiet, cozy street that's just moments from the Boardwalk. This is the perfect listing if you're a respectful, responsible guy/gal! This is the front apartment on the first floor of a former single-family home. It was renovated just a few years ago with new flooring, appliances, etc. Lots of natural light and ocean breezes. Furnished in a clean, modern aesthetic with relaxation in mind. Guests have access to wifi, kitchen, basic pantry supplies, clean linens/towels, and a bit of closet space. Out of respect to my neighbors, shared washer/dryer and communal outdoor spaces are off-limits. I'll meet with you to get you settled in. After that, the place is all yours. I'll be available by phone and text if any issues arise. This is a very walkable neighborhood with lots of great restaurants and nightlife. Oh, and the beach, of course. The Venice Boardwalk is just around the corner and it's a 10-minute walk to Abbo2015-06-15ttNaN2014-04-04f2016-07-2433.9876-118.4745Luxurious and quiet - 30 second walk to the beach!Venice1298.0000NaN902911.00001.0000199.0000
230190ApartmentEntire home/apt{TV,Internet,"Wireless Internet","Air conditioning","Wheelchair accessible",Kitchen,"Pets allowed",Elevator,"Buzzer/wireless intercom",Heating,"Family/kid friendly",Washer,Dryer,"Smoke detector","Carbon monoxide detector","First aid kit","Safety card","Fire extinguisher",Essentials,Shampoo,"24-hour check-in",Hangers,Iron,"Laptop friendly workspace"}41.0000Real BedstrictTrueNYCMy studio is located in the heart of Bensonhurst - Little Italy and small Chinatown of Brooklyn. It's cozy and comfortable place to stay short term! My studio is located in the heart of Bensonhurst - Little Italy and small Chinatown of Brooklyn. It's cozy and comfortable place to stay short term! The space is great for a small party and it's well equipped with amenities and it has pretty much everything a guest might need for a good rest. The guest has a access to an entire home! I am always available for communication, any time a guest needs help I will be there 24/7 The area is very multicultural; it's just a 5 min walk from Bensonhurst park and Verrazano bridge Boardwalk- the park itself very close to the ocean. The area has all possible shopping and the prices are the lowest in town! The commute is very easy - it's a plenty of buses around BK plus D/N train and only 35 minutes from midtown Manhattan! Car services are all over as well! There's a fire escape outside the window - plea2016-01-03tf80%2015-09-02f2017-08-0140.6026-73.9933Bensonhurst STYLISH STUDIOBensonhurst2694.0000https://a0.muscache.com/im/pictures/bf8ee448-b113-46cd-aeed-705825ec52e6.jpg?aki_policy=small112140.00002.000085.0000
343181TownhousePrivate room{"Wireless Internet","Air conditioning","Pets live on this property",Cat(s),"Hot tub",Heating,"Smoke detector","Carbon monoxide detector",Essentials,Shampoo,"Lock on bedroom door",Hangers,"Hair dryer","Laptop friendly workspace","translation missing: en.hosting_amenity_49","translation missing: en.hosting_amenity_50"}31.0000Real BedstrictTrueLA我们位于洛杉矶圣盖博市,距离夏威夷超市,99大华超市,顺发超市(全部为华人超市,语言沟通无障碍)步行十分钟距离,离costco,targte,walmart圣盖博医院丶嘉惠尔医院不到十分钟的车程。封闭小区,安全铁门。交通便利,超市丶餐馆丶医院丶公交车站都在步行距离,即使无车代步依然出入自如,让您出行方便。我们了解您拎包入住的需求,设施齐全,水电网络,家电家具,床上用品一应俱全,干净卫生,让您居住安全无忧。独立卫生间。 Private bathroom。 本房间内有两张床,一张Queen Size,一张Twin Size. zh.airbnb.com/c/shaohuac2 用此链接注册可获得$30美元住房基金用于订房! 我们位于洛杉矶圣盖博市,距离夏威夷超市,九九大华超市,顺发超市(全部为华人超市,语言沟通无障碍)步行十分钟距离,离costco,target,walmart圣盖博医院丶嘉惠尔医院不到十分钟的车程。封闭小区,安全铁门。交通便利,超市丶餐馆丶医院丶公交车站都在步行距离,即使无车代步依然出入自如,让您出行方便。 我们了解您拎包入住的需求,设施齐全,水电煤网络,家电家具,床上用品一应俱全,同,贴心舒适丶干净卫生,让您居住安全无忧。 自有卫生间,大浴室,冲浪浴缸! 全新家私以及床上用品,包水电,宽带,24小时热水,楼下有专门的客用微波炉以及冰箱。 1 mile to the GYM, AMC theater & shops in San Gabriel Square > 3 mile to CSULA & ELAC (bus #70 & 770) > 5 mile to USC medical center (bus #70 to the door) > 7 mile to downtown L A > 10 mile to USC Main campus > 12 mile to Hollywood area & Thai Town2016-06-16tt100%2016-03-17f2017-03-2934.0727-118.0965LA San Gabriel Suit room 圣盖博大套房 免费停车 Free ParkingSan Gabriel3395.0000https://a0.muscache.com/im/pictures/0cff238c-a526-4c07-85d8-1d6522de7892.jpg?aki_policy=small917761.00002.000070.0000
462109CondominiumEntire home/apt{TV,"Cable TV",Internet,"Wireless Internet","Air conditioning",Kitchen,"Free parking on premises","Buzzer/wireless intercom",Heating,"Family/kid friendly",Washer,Dryer,"Smoke detector","Carbon monoxide detector",Essentials,Shampoo,Hangers,"Hair dryer",Iron}52.0000Real BedstrictTrueChicagoLocated in the heart of the bustling Woodlawn/Hyde park Area. Just a 10 minute drive to the beaches and running trails of Lake Michigan and Grant Park. Conveniently located near public transit and the well renowned Museum of Science and Industry. UPSCALE AMENITIES!!! Why stay at a hotel! The location of this condo is within walking distance of the University of Chicago. The renovated brick condominium features 2 Bedrooms with en Suite Bathrooms. The Master Bedroom is furnished with a REAL Queen size bed. The 2nd bedroom has a REAL QUEEN SIZE BED. The Master Bathroom is equipped with a jacuzzi bathtub to provide additional relaxation during your vacation or staycation. The furnished guestrooms include flat screen television and dvd player. The unit has a modern kitchen, washer and dryer, common area and sunroom. There is also a shared rear patio. Everything in the unit is included in your stay. Ample Parking , Internet, linens, etc, etc. We are a text or phone call away if help is2015-07-31tt100%2015-02-10t2017-03-1941.7819-87.6063XTRA Large 2bdrm 2bath in the City near "El" TrainWoodlawn6088.0000https://a0.muscache.com/im/pictures/92108903/0b86d70a_original.jpg?aki_policy=small606372.00002.000072.0000
51178ApartmentEntire home/apt{TV,"Cable TV",Internet,"Wireless Internet","Air conditioning",Kitchen,Breakfast,"Buzzer/wireless intercom",Heating,"Family/kid friendly","Smoke detector","Carbon monoxide detector","First aid kit","Safety card","Fire extinguisher",Essentials,Shampoo}51.0000Real BedstrictTrueNYCSteps away from some of the best UES restaurants and minutes from two of my favorite museums. The area has so much to offer. My apt is on a quiet street, has exposed brick and the neighborhood makes you feel like you are a New Yorker during your stayNaNtfNaN2015-04-19fNaN40.7793-73.9473Cozy & convenient UES 2BR near all!Upper East Side0NaNhttps://a0.muscache.com/im/pictures/83993776/de87ff9a_original.jpg?aki_policy=small101282.00003.0000305.0000
647881ApartmentEntire home/apt{"Wireless Internet",Kitchen,"Free parking on premises",Heating,"Family/kid friendly","Smoke detector",Essentials,Hangers,"Hair dryer",Iron,"Laptop friendly workspace","Private entrance"}41.0000Real BedstrictTrueNYCHello Travelers! This cozy clean and beautiful apartment features lots of light and comfortable beds. There is enough place for 4. The clean, bright and beautifully decorated apartment is located on the first floor and is very child-friendly. I am offering a beautiful, big, clean apartment available for rent with a bathroom that includes a shower, toilet and sink. I will be gone on the from October 6th to 11th (I will be back on the 11th), so these are the only dates that work. Please do not contact me for other dates. I will NOT be there. You have the entire apartment to yourself. The apartment has a bedroom with a huge canopy bed, then there is a comfortable couch in the living room and another double loft bed in my son's room. His room can also be used by families. There is tons of toys! The apartment is filled with sunlight and very clean and comfortable. There is basic cable, high speed DSL internet and a full size kitchen with a dishwasher. All in all a wonderful place in centra2017-04-01tt100%2014-03-19f2017-05-3040.6773-73.9431Beautiful and Clean Apt with Tons of Light!Crown Heights3100.0000https://a0.muscache.com/im/pictures/6e26b475-0dca-49a1-8bbe-68e6c6bd4ca7.jpg?aki_policy=small11216.02.00002.0000120.0000
765143HousePrivate room{TV,"Cable TV","Wireless Internet","Air conditioning",Kitchen,"Free parking on premises","Pets allowed","Pets live on this property",Cat(s),Heating,Washer,Dryer,"Smoke detector","Carbon monoxide detector","First aid kit",Essentials,Shampoo,Hangers,"Hair dryer",Iron,"Private living room",Bathtub,"Game console","Hot water","Bed linens","Extra pillows and blankets","Ethernet connection",Microwave,"Coffee maker",Refrigerator,Dishwasher,"Dishes and silverware","Cooking basics",Oven,Stove,"Patio or balcony","Luggage dropoff allowed"}21.0000Real BedflexibleTrueBostonExplore Boston & the surrounding areas from this cozy Brighton apartment. The space is bright and open with lots of natural light, the room is clean and functional (with a super comfy bed!), and the hosts are courteous and easygoing. Enjoy easy access to downtown Boston, Cambridge, and more without all the noise and fuss of city living. If you are looking for a quaint, clean, quiet place to rest your head, look no further! While staying with us, you will have your own private guest bedroom, furnished with a full size bed, an empty dresser, and foldable table and chairs. There is an AC unit and central heat in the room (for that notoriously unpredictable Boston weather!). We also provide clean bedding, an alarm clock, and a basket of toiletries for each guest. You are also completely welcome and encouraged to use the shared spaces including the bathroom, kitchen, living spaces, and laundry (which is free and in the building). In the apartment with you will be your two hosts and two oth2017-07-14tf100%2017-03-29t2017-08-2342.3532-71.1556Cozy Brighton GetawayAllston-Brighton1195.0000https://a0.muscache.com/im/pictures/166fcee4-ff54-4f2e-aad9-392b778c0708.jpg?aki_policy=small021351.00001.000059.0000
850970ApartmentPrivate room{"Wireless Internet","Air conditioning",Kitchen,"Smoking allowed","Pets allowed","Buzzer/wireless intercom","Family/kid friendly","Smoke detector","Carbon monoxide detector",Essentials,Hangers,"Laptop friendly workspace","translation missing: en.hosting_amenity_50"}21.0000Real BedflexibleFalseNYCGreat space in a two bedroom apartment in Brooklyn available for rent. Currently there is one kind size bed however it can be split up into two single beds based on preference. There is a communal backyard in the building and rooftop access. 5 minute walk to the Central M subway stop and 10 minute walk to the Morgan L or Myrtle-Broadway J stop. Lovely coffee shops and bars nearby.NaNtfNaN2014-10-05fNaN40.7006-73.9297Spacious Bedroom Fits 2 PeopleBushwick0NaNhttps://a0.muscache.com/im/pictures/6182b137-55f0-44ed-a1af-440c4e45c915.jpg?aki_policy=small112061.00002.000075.0000
9603ApartmentPrivate room{Internet,"Wireless Internet","Air conditioning","Wheelchair accessible",Kitchen,Elevator,Heating,"Family/kid friendly",Washer,Dryer,"Smoke detector",Essentials,Shampoo,Hangers,"Hair dryer","Laptop friendly workspace","translation missing: en.hosting_amenity_50"}21.0000Real BedstrictTrueNYCHello There! My name is Tiffany and I have a beautiful and comfortable home on the Roosevelt Island. My place is super convenient for you and your friends who are visiting this amazing city. It is only one stop from Manhattan, 6 mins walk to F train subway station, 15 mins to Times Squares and most everywhere in the city! You’ll love my place because of the great river views from your room, two single beds in the private room. Perfect option for solo adventurers/ business travelers/ friends! Unique and outstanding views of the East & Hudson Rivers and Manhattan from Roosevelt Island Grocery Stores, Pharmacy, Starbucks, Pizza, Diner, Japanese Restaurant, Chinese Takeout, Dry Cleaner, Shoe Repair, all within walking distance on the island Amish Farmers Market Saturdays 6am-4pm Riverside promenades perfect for jogging, taking walks, as well as picnic areas My apartment is close to F train subway station, and it could take you everywhere in the city. You can also take Roosevelt Island Tr2017-03-05tf93%2014-08-27f2017-09-1840.7634-73.9494Wonderful island life in NYC areaRoosevelt Island3896.0000https://a0.muscache.com/im/pictures/fa1ca2a7-5056-4fb7-8001-874969bbc01e.jpg?aki_policy=small100441.00002.000075.0000
idproperty_typeroom_typeamenitiesaccommodatesbathroomsbed_typecancellation_policycleaning_feecitydescriptionfirst_reviewhost_has_profile_pichost_identity_verifiedhost_response_ratehost_sinceinstant_bookablelast_reviewlatitudelongitudenameneighbourhoodnumber_of_reviewsreview_scores_ratingthumbnail_urlzipcodebedroomsbedsprice
5927849201HouseEntire home/apt{TV,"Cable TV",Internet,"Wireless Internet",Kitchen,"Free parking on premises","Indoor fireplace",Heating,Washer,Dryer,"Smoke detector","Carbon monoxide detector","First aid kit","Fire extinguisher",Essentials,Shampoo,"24-hour check-in",Hangers,"Hair dryer",Iron,"Laptop friendly workspace","Self Check-In",Keypad,"Private entrance"}21.0000Real BedmoderateTrueSFMy cute little house is in a great neighborhood close to everything San Francisco has to offer. Major bus and train lines are on the next block, but there are lots of shops and restaurants within walking distance. Duboce Park is across the street. A 1/1 with a loft, garage and small backyard. The bathroom is off the bedroom on the ground floor. You must go through the bedroom to get to the bathroom. There is a queen size sleep number bed you can adjust to your liking and a full size washer and dryer. Upstairs is a comfy queen size sleeper sofa, living room and fully equipped kitchen. The loft above has a full size bed. Large south facing windows make it nice and sunny. There's a small balcony that has an outdoor grill. Premium cable TV/DVR and high speed wifi. Private access to the whole house including the garage (if needed) and backyard. I have a mini cooper, but the garage can fit something a little bigger. If you need to use the garage, let me know when you book. The larg2014-12-19tt100%2014-09-08f2017-09-2237.7694-122.4303In the center of the city!Duboce Triangle5798.0000https://a0.muscache.com/im/pictures/62679478/b00201e0_original.jpg?aki_policy=small94117.01.00002.0000225.0000
5927910637HouseEntire home/apt{TV,"Wireless Internet","Air conditioning",Kitchen,"Free parking on premises","Indoor fireplace","Family/kid friendly",Washer,Dryer,"First aid kit","Fire extinguisher",Essentials,Shampoo,"Hair dryer",Iron,"Laptop friendly workspace","translation missing: en.hosting_amenity_49"}41.0000Real BedstrictFalseLAThis perfectly preserved specimen of Mid Century Modern / Usonian architecture is now available at hourly or daily rates for productions, photo shoots and small dinner or cocktail events. 4 miles from downtown, this historic monument features a zen garden entrance, panoramic windows, soaring views, cantilevered overhangs, celerestory windows, horizontal wood paneled walls, a huge sliding glass door leading to an outdoor living space and succulent draped terrace. Please message for terms/rates.NaNtt100%2016-07-03fNaN34.0988-118.2108PRODUCTION/EVENT LOCATION:Pristine Mid Century GemMount Washington0NaNhttps://a0.muscache.com/im/pictures/619ecc00-8606-4b4e-8622-84c70a84aebd.jpg?aki_policy=small900652.00002.0000500.0000
592803930ApartmentEntire home/apt{TV,"Cable TV",Internet,"Wireless Internet",Kitchen,"Free parking on premises","Pets allowed",Heating,"Suitable for events",Washer,Dryer,"Smoke detector","Carbon monoxide detector","First aid kit","Fire extinguisher",Essentials,Shampoo,"24-hour check-in",Hangers,"Hair dryer",Iron,"Laptop friendly workspace","translation missing: en.hosting_amenity_49","translation missing: en.hosting_amenity_50"}42.0000Real BedstrictTrueLABrand New Lux/Mod Beach Rental right on the famous Venice Grand Canal! Luxurious, high-end and full of opulent vacation features. Cooks kitchen, steam shower and soaktub. disappearing walls of glass. This place has it all! Come share our spa-home! A recent beams-out remodel, we spared no expense to make this a luxurious beach get-away. Throw open the accordion walls of glass and let the inside out, and the gorgeous outside view in! Either I will be your concierge or one of my friendly helpful staff from work will be available for your needs. The Marina Del Rey beach is the most beautiful, cleanest and quietest around. But if you want more action, bohemian Venice is a short walk away. Enjoy the quiet luxury of our canal-front home or stroll or bike to over 100 great restaurants and night spots. See out guide attached to this listing for some of faves! UBERs abound. Never more than a few minutes away. Sure you can hop the bus, but better off parking the car and walking or biking. There's2015-03-28tt100%2014-10-27f2017-04-2333.9773-118.4614LUX Marina Beach 2+2 on the CanalsMarina Del Rey3399.0000https://a0.muscache.com/im/pictures/81405037/3e46f682_original.jpg?aki_policy=small902922.00002.0000380.0000
5928114939ApartmentPrivate room{"Wireless Internet",Kitchen,"Pets live on this property",Cat(s),Heating,Washer,Dryer,"Smoke detector","First aid kit","Safety card","Fire extinguisher",Shampoo,"Lock on bedroom door","24-hour check-in"}22.0000Real BedstrictFalseNYCCozy, beautiful and sunny bedroom. Just one block from amazing A express line and few blocks from the red line. Next to Saint Nicholas Park and wonderful jazz restaurant LA MAISON. Great living room and kitchen :)NaNttNaN2014-04-24fNaN40.8150-73.9525Cozy Room Upper West ManhattanHarlem0NaNhttps://a0.muscache.com/im/pictures/cad09eb8-a226-4381-892b-66a27e3677c5.jpg?aki_policy=small100271.00001.000055.0000
5928221600ApartmentEntire home/apt{TV,"Cable TV",Internet,"Wireless Internet","Air conditioning",Kitchen,"Free parking on premises","Buzzer/wireless intercom",Heating,"Family/kid friendly",Washer,Dryer,"Smoke detector","First aid kit","Fire extinguisher",Essentials,Shampoo}72.0000Real BedstrictTrueLALarge 2 bdrm very Confortable. Centrally located next to charming Park. Walk to Top Shops, Dine & Entertainment at The Americana at Brand and Glendale Galleria. Short drive to Downtown LA, Dodgers Stadium, Hollywood, Pasadena, Universal Studios, etc. This is a 2 bedroom/two bathroom very spacious Apt fully furnished and fully equipped. Large kitchen, 6 chair dinner set, comfortable living room. In unit washer/dryer, air-conditioning, heat, dishwasher, and garbage disposal, also has high-speed wireless internet. Under building private parking. BED LAYOUT: Master bedroom with a Calif King bed 2nd Bedroom with two twin beds or put together to make it a King + also in 2nd bedroom a futon for a small person Living-room has a full size futon, could sleep 2 average size persons - Can also provide a baby crib/playpen and umbrella stroller for a child upon request Conveniently located just minutes from two major freeways (134 & 5), and just a few minutes from ABC, Disney and Universal Studi2015-06-19tt100%2014-12-10t2017-03-2834.1441-118.26152bd Apt w/Parking / Prime LocationGlendale797.0000https://a0.muscache.com/im/pictures/76169952/3207e0ea_original.jpg?aki_policy=small912042.00005.0000214.0000
5928364666HouseEntire home/apt{TV,"Cable TV",Internet,"Wireless Internet","Air conditioning",Kitchen,"Free parking on premises","Smoking allowed","Pets allowed",Gym,"Hot tub",Heating,"Family/kid friendly",Washer,Dryer,"Smoke detector","Carbon monoxide detector","First aid kit","Fire extinguisher",Essentials,Shampoo,"Lock on bedroom door",Hangers,"Laptop friendly workspace"}52.0000Real BedmoderateTrueLAOur newly renovated House is in the Lake Balboa area in the San Fernando Valley. Open floor plan, updated kitchen and huge zen yard with hot tub! A very short drive from gorgeous Balboa Park and close to both the 405 & 101 freeways. Very large and updated house! The master bedroom has a king-sized memory foam bed, seating area and the second bedroom has a queen sized bed plus desk. Additionally there is an office with twin sleeper couch and desk. Completely renovated and updated kitchen with stainless steel appliances. Large backyard with outdoor dining, hot tub, hammock & multiple seating areas. High-speed internet & wifi. Home gym in garage with elliptical machine & free weights & flat screen tv. Record player with 200+ albums! Guests will have access to all of the house except the master walk in closet, which will be used for storage. Garage is not used for parking since there is a home gym inside. We will not be present in Southern California but are very communicative an2016-04-11tt100%2011-08-23f2017-01-3134.1988-118.5020Lake Balboa House / Zen Retreat!Lake Balboa588.0000https://a0.muscache.com/im/pictures/61891002/232f6a5e_original.jpg?aki_policy=small914063.00003.0000225.0000
5928410864CondominiumEntire home/apt{TV,"Cable TV","Wireless Internet","Air conditioning",Kitchen,"Indoor fireplace",Heating,Washer,Dryer,"Smoke detector","Carbon monoxide detector","First aid kit","Fire extinguisher",Essentials,Shampoo,Hangers,"Hair dryer",Iron,"Laptop friendly workspace","translation missing: en.hosting_amenity_49","translation missing: en.hosting_amenity_50",Bathtub,"Window guards","Hot water","Bed linens","Extra pillows and blankets",Microwave,"Coffee maker",Refrigerator,Dishwasher,"Dishes and silverware","Cooking basics",Oven,Stove,"Patio or balcony","Long term stays allowed"}21.5000Real BedstrictTrueNYCBeautiful modern duplex in old traditional Harlemite Brownstone from 1906. Private beautiful quiet terrace with lounge chair, table and seats. Kitchen equipped with modern appliances (toaster, oven, microwave, juicer and blender). One queen size bed in the bedroom only so it's for 1 person or a couple. There is a washer and dryer inside the apartment. It has one bathroom downstairs and full bathroom upstairs. AC, Heat, Wifi, full cable (HBO included), iron, hair dryer... all is there. The terrace is amazing and very relaxing. You are allowed to smoke there only. There is also a desk upstairs by the terrace so you can work with the door open. Full apartment I will be traveling so a friend of mine will meet you to give you the keys. Check out will be by yourself. Whole Food Market is 3 minutes away. The neighborhood has so many cool restaurants and bars (Red Rooster, Vinateria, Lido, Maison Harlem and many more...). The best pancakes are at Community Food Best Cookies: Levain 3 minutes2017-08-04tt100%2010-07-02f2017-09-1040.8077-73.9524Modern Beautiful Duplex in BrownstoneHarlem11100.0000https://a0.muscache.com/im/pictures/8dda462d-64e0-48c5-9853-dd8c20306609.jpg?aki_policy=small100271.00001.0000200.0000
5928514978ApartmentEntire home/apt{TV,Internet,"Wireless Internet","Air conditioning",Kitchen,"Free parking on premises",Heating,"Family/kid friendly",Washer,Dryer,"Smoke detector","Carbon monoxide detector",Essentials,Shampoo,"Lock on bedroom door","24-hour check-in",Hangers,"Hair dryer",Iron,"Laptop friendly workspace"}31.0000Real BedmoderateTrueLAExplore Los Angeles with your own private cottage-like oasis on the Westside! This centrally located, peaceful, and spacious unit is the ideal place to rest your head, prepare your own meals, swing under the orange trees, and veg out with a 58" smart tv. - 4 miles to beach/Venice - 5 blocks to Santa Monica - 3 miles to Westwood - 20 min to Hollywood + Beverly Hills - Queen-Sized Posturepedic bed - Stand Alone Unit - No Shared Walls - Completely Private - Secure, Covered Parking Hello! Welcome to my artsy cottage-like apartment on the Westside. This unit is centrally located with easy freeway access and right next to LA's new Expo Line/bike path that flows between Downtown LA and Santa Monica. My peaceful apartment is spacious, yet cozy, providing all essential amenities including a full kitchen (cookware, coffee maker, tea kettle, etc), dining room, private bathroom, living room (equipped with a brand new 58" smart tv) with a very cozy boho couch, wifi, and a bedroom looking out inNaNtt33%2015-01-05fNaN34.0305-118.4445Artsy and Spacious Back HouseWest Los Angeles0NaNhttps://a0.muscache.com/im/pictures/d807e712-d965-4243-bdc7-cbffff311fa4.jpg?aki_policy=small900641.00002.0000135.0000
5928658971ApartmentEntire home/apt{TV,"Wireless Internet","Air conditioning","Wheelchair accessible",Kitchen,Elevator,"Buzzer/wireless intercom",Heating,"Family/kid friendly","Smoke detector","Carbon monoxide detector","First aid kit","Safety card","Fire extinguisher",Essentials,Shampoo,"Lock on bedroom door","24-hour check-in",Hangers,"Hair dryer",Iron,"Laptop friendly workspace","Self Check-In",Lockbox}31.0000Real BedstrictTrueNYCQuiet 1 bedroom apartment located in luxury complex. Queen size bed and couch for any additional guests. 2 Minute walk to J & M subway line. 1 minute walk to broadway featuring restraunts , cafes, shopping, grocery stores, banks, & Bus lines. Parking on Street Elevator in Building Safe & secure building. Individual lock and key on bedroom door for extra security. My place is good for artists, adventurers, vacationers, and business travelers.2016-11-27tt86%2014-08-13f2017-08-1240.7005-73.9391Cozy Apartment off J&M Subway LinesBushwick11100.0000https://a0.muscache.com/im/pictures/0246b6ff-f116-4281-bbfd-8902e412874b.jpg?aki_policy=small112061.00001.0000115.0000
5928735007HouseEntire home/apt{TV,"Cable TV",Internet,"Wireless Internet","Air conditioning",Kitchen,"Pets allowed","Hot tub",Heating,"Family/kid friendly",Washer,Dryer,"Smoke detector","Carbon monoxide detector",Essentials,Shampoo,"24-hour check-in",Hangers,"Hair dryer",Iron,"Laptop friendly workspace","Self Check-In",Lockbox,"Private entrance",Bathtub,"Pack ’n Play/travel crib"}143.0000Real BedstrictTrueLACome stay in this nice and spacious 4 bedroom home located in one of the best areas of Los Angeles. this home is within 15 to 20 minutes of the beach, Hollywood, Beverly Hills and downtown LA. This home can accommodate 10 people comfortably and up to 12 with air / floor mats. SPACIOUS CLUBHOUSE-STYLE 4 BEDROOM + 3 BATHROOM HOUSE WITH LOTS OF LIGHT AND LOCATED IN THE HIGHLY SOUGHT-AFTER AREA OF PICO ROBERTSON. Very central location to all of LA - Located at La Cienega and Airdrome next to Chabad of Sola. Great neighborhood in walking distance to kosher restaurants and markets. Very centrally located in LA and next to Beverly Hills. A great location to most sightseeing spots in Los Angeles RENTAL HIGHLIGHTS INCLUDE: Spacious and bright house in the heart of everything 'LA' Recently updated: bathroom, kitchen, sheets, towels, and pillows Full kitchen Wood floors Living room area 3 Queen beds + 1 Full bed + Queen Sofa Bed. House can sleep up to 10 with current beds and up to 14 with2015-07-23tt84%2014-08-15f2016-06-2634.0465-118.3770KOSHER-FRIENDLY 4 BEDROOM SLEEPS 10 and up to 12NaN693.0000NaN900354.00005.0000360.0000